Documentation re-generated, a lot of minor stuff

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blacklight 2009-08-16 20:57:15 +02:00
parent d52976e74e
commit 7861e56f35
144 changed files with 2589 additions and 851 deletions

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@ -6,6 +6,7 @@
neurons, in the output layer.
Oh, and I've fixed too that nasty bug that made training from sets
containing more than a single training set.
Added examples in the Doxygen documentation.
* neuron.cpp: Fixing propagate() function
2009-08-15 BlackLight <blacklight@autistici.org>

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@ -30,7 +30,6 @@ install:
install -m 0644 lib${LIB}.a ${PREFIX}/lib/lib${LIB}.a
install -m 0644 ${INCLUDEDIR}/${LIB}.hpp ${PREFIX}/${INCLUDEDIR}
install -m 0644 ${INCLUDEDIR}/${LIB}_exception.hpp ${PREFIX}/${INCLUDEDIR}
install -m 0644 ${PREFIX}/share/${LIB}/README
ln -sf ${PREFIX}/lib/lib${LIB}.so.0.0.0 ${PREFIX}/lib/lib${LIB}.so.0
uninstall:

23
README
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@ -1,17 +1,28 @@
=======================================================
_ _ _ _ _ _
| (_) |__ | \ | | ___ _ _ _ __ __ _| | _ _
| | | '_ \| \| |/ _ \ | | | '__/ _` | | _| |_ _| |_
| | | |_) | |\ | __/ |_| | | | (_| | ||_ _||_ _|
|_|_|_.__/|_| \_|\___|\__,_|_| \__,_|_| |_| |_|
=======================================================
C++ class for managing neural networks, by BlackLight < blacklight@autistici.org >
Released under GNU GPL licence v.3, copyright 2008-2009
> To install:
$ make
# make install
-> goto INSTALL
> To link programs with it:
g++ <options and files> -lneural++
> HOWTO:
# Take a look to the example in "example" directory to view it pratically.
# Take a look to the example in "examples" directory in the source package, in
$PREFIX/share/neural++ or at http://0x00.ath.cx/prog/neuralpp/examples .
# Take a look to documentation in "doc" directory to see how to use it. You can
also generate documentation on your own, moving to `include` directory and typing
`doxygen`
# Take a look to the example in "doc" directory in the source package, in
$PREFIX/share/neural++ or at http://0x00.ath.cx/prog/neuralpp/doc/index.html.
You can also generate the documentation on your own moving to include/
directory in the source package and typing `doxygen`, if you've got doxygen
installed.

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@ -12,6 +12,7 @@
<li><a href="namespaces.html"><span>Namespaces</span></a></li>
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<li class="current"><a href="files.html"><span>Files</span></a></li>
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</ul>
</div>
<h1>Markup.h</h1><a href="Markup_8h.html">Go to the documentation of this file.</a><div class="fragment"><pre class="fragment"><a name="l00001"></a>00001 <span class="comment">// Markup.h: interface for the CMarkup class.</span>
@ -660,7 +661,7 @@
<a name="l00644"></a>00644
<a name="l00645"></a>00645 <span class="preprocessor">#endif // !defined(_MARKUP_H_INCLUDED_)</span>
</pre></div></div>
<hr size="1"><address style="text-align: right;"><small>Generated on Sat Aug 15 02:56:02 2009 for Neural++ by&nbsp;
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@ -12,6 +12,7 @@
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@ -1031,7 +1032,7 @@
</div>
</div><p>
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<hr size="1"><address style="text-align: right;"><small>Generated on Sat Aug 15 02:56:02 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
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@ -0,0 +1,25 @@
<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN">
<html><head><meta http-equiv="Content-Type" content="text/html;charset=UTF-8">
<title>Neural++: /examples/learnAdd.cpp</title>
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<h1>/examples/learnAdd.cpp</h1><div class="fragment"><pre class="fragment"></pre></div> </div>
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:30:49 2009 for Neural++ by&nbsp;
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@ -34,9 +35,14 @@
<tr><td class="indexkey"><a class="el" href="structCMarkup_1_1SavedPosMap.html">CMarkup::SavedPosMap</a></td><td class="indexvalue"></td></tr>
<tr><td class="indexkey"><a class="el" href="structCMarkup_1_1SavedPosMapArray.html">CMarkup::SavedPosMapArray</a></td><td class="indexvalue"></td></tr>
<tr><td class="indexkey"><a class="el" href="structCMarkup_1_1TokenPos.html">CMarkup::TokenPos</a></td><td class="indexvalue"></td></tr>
<tr><td class="indexkey"><a class="el" href="classneuralpp_1_1InvalidSynapticalWeightException.html">neuralpp::InvalidSynapticalWeightException</a></td><td class="indexvalue">Exception raised when, while trying the network or directly, the weight of a synapsis is set to a value |w| &gt; 1 </td></tr>
<tr><td class="indexkey"><a class="el" href="classneuralpp_1_1InvalidXMLException.html">neuralpp::InvalidXMLException</a></td><td class="indexvalue">Exception thrown when trying parsing an invalid XML </td></tr>
<tr><td class="indexkey"><a class="el" href="classneuralpp_1_1Layer.html">neuralpp::Layer</a></td><td class="indexvalue">Class for managing layers of neurons </td></tr>
<tr><td class="indexkey"><a class="el" href="structMCD__CSTR.html">MCD_CSTR</a></td><td class="indexvalue"></td></tr>
<tr><td class="indexkey"><a class="el" href="structneuralpp_1_1netrecord.html">neuralpp::netrecord</a></td><td class="indexvalue"></td></tr>
<tr><td class="indexkey"><a class="el" href="classneuralpp_1_1NetworkFileNotFoundException.html">neuralpp::NetworkFileNotFoundException</a></td><td class="indexvalue">Exception thrown when doing an attempt to load a network from an invalid file </td></tr>
<tr><td class="indexkey"><a class="el" href="classneuralpp_1_1NetworkFileWriteException.html">neuralpp::NetworkFileWriteException</a></td><td class="indexvalue">Exception thrown when trying to write the network's information to a file that cannot be written </td></tr>
<tr><td class="indexkey"><a class="el" href="classneuralpp_1_1NetworkIndexOutOfBoundsException.html">neuralpp::NetworkIndexOutOfBoundsException</a></td><td class="indexvalue">Exception raised when trying to access a neuron whose index is larger than the number of neurons in the network </td></tr>
<tr><td class="indexkey"><a class="el" href="classneuralpp_1_1NeuralNet.html">neuralpp::NeuralNet</a></td><td class="indexvalue">Main project's class </td></tr>
<tr><td class="indexkey"><a class="el" href="classneuralpp_1_1Neuron.html">neuralpp::Neuron</a></td><td class="indexvalue">Class for managing neurons </td></tr>
<tr><td class="indexkey"><a class="el" href="structneuralpp_1_1neuronrecord.html">neuralpp::neuronrecord</a></td><td class="indexvalue"></td></tr>
@ -44,7 +50,7 @@
<tr><td class="indexkey"><a class="el" href="structneuralpp_1_1synrecord.html">neuralpp::synrecord</a></td><td class="indexvalue"></td></tr>
</table>
</div>
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@ -212,7 +213,7 @@
<tr class="memlist"><td><a class="el" href="classCMarkup.html#f3b30bc5314bbc8d157dca6d924f4852">x_WriteText</a>(const MCD_STR &amp;strDoc, FilePos &amp;file)</td><td><a class="el" href="classCMarkup.html">CMarkup</a></td><td><code> [protected, static]</code></td></tr>
<tr class="memlist"><td><a class="el" href="classCMarkup.html#8aa2cd9b38b3e173d2149914c59eb2b7">~CMarkup</a>()</td><td><a class="el" href="classCMarkup.html">CMarkup</a></td><td><code> [inline]</code></td></tr>
</table></div>
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<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
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@ -4478,7 +4479,7 @@
<hr>The documentation for this class was generated from the following file:<ul>
<li><a class="el" href="Markup_8h-source.html">Markup.h</a></ul>
</div>
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<h1>neuralpp::InvalidSynapticalWeightException Member List</h1>This is the complete list of members for <a class="el" href="classneuralpp_1_1InvalidSynapticalWeightException.html">neuralpp::InvalidSynapticalWeightException</a>, including all inherited members.<p><table>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1InvalidSynapticalWeightException.html#42e54de0ef9d9f711a483287f4f95916">InvalidSynapticalWeightException</a>()</td><td><a class="el" href="classneuralpp_1_1InvalidSynapticalWeightException.html">neuralpp::InvalidSynapticalWeightException</a></td><td><code> [inline]</code></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1InvalidSynapticalWeightException.html#8d374dd7e8363b2551ae6e306b11473a">what</a>() const </td><td><a class="el" href="classneuralpp_1_1InvalidSynapticalWeightException.html">neuralpp::InvalidSynapticalWeightException</a></td><td><code> [inline]</code></td></tr>
</table></div>
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<h1>neuralpp::InvalidSynapticalWeightException Class Reference</h1><!-- doxytag: class="neuralpp::InvalidSynapticalWeightException" -->Exception raised when, while trying the network or directly, the weight of a synapsis is set to a value |w| &gt; 1.
<a href="#_details">More...</a>
<p>
<code>#include &lt;<a class="el" href="neural_09_09__exception_8hpp-source.html">neural++_exception.hpp</a>&gt;</code>
<p>
<p>
<a href="classneuralpp_1_1InvalidSynapticalWeightException-members.html">List of all members.</a><table border="0" cellpadding="0" cellspacing="0">
<tr><td></td></tr>
<tr><td colspan="2"><br><h2>Public Member Functions</h2></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1InvalidSynapticalWeightException.html#42e54de0ef9d9f711a483287f4f95916">InvalidSynapticalWeightException</a> ()</td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">const char *&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1InvalidSynapticalWeightException.html#8d374dd7e8363b2551ae6e306b11473a">what</a> () const throw ()</td></tr>
</table>
<hr><a name="_details"></a><h2>Detailed Description</h2>
Exception raised when, while trying the network or directly, the weight of a synapsis is set to a value |w| &gt; 1. <hr><h2>Constructor &amp; Destructor Documentation</h2>
<a class="anchor" name="42e54de0ef9d9f711a483287f4f95916"></a><!-- doxytag: member="neuralpp::InvalidSynapticalWeightException::InvalidSynapticalWeightException" ref="42e54de0ef9d9f711a483287f4f95916" args="()" -->
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<td class="memname">neuralpp::InvalidSynapticalWeightException::InvalidSynapticalWeightException </td>
<td>(</td>
<td class="paramname"> </td>
<td>&nbsp;)&nbsp;</td>
<td><code> [inline]</code></td>
</tr>
</table>
</div>
<div class="memdoc">
<p>
</div>
</div><p>
<hr><h2>Member Function Documentation</h2>
<a class="anchor" name="8d374dd7e8363b2551ae6e306b11473a"></a><!-- doxytag: member="neuralpp::InvalidSynapticalWeightException::what" ref="8d374dd7e8363b2551ae6e306b11473a" args="() const " -->
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<td class="memname">const char* neuralpp::InvalidSynapticalWeightException::what </td>
<td>(</td>
<td class="paramname"> </td>
<td>&nbsp;)&nbsp;</td>
<td> const throw ()<code> [inline]</code></td>
</tr>
</table>
</div>
<div class="memdoc">
<p>
</div>
</div><p>
<hr>The documentation for this class was generated from the following file:<ul>
<li><a class="el" href="neural_09_09__exception_8hpp-source.html">neural++_exception.hpp</a></ul>
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<h1>neuralpp::InvalidXMLException Member List</h1>This is the complete list of members for <a class="el" href="classneuralpp_1_1InvalidXMLException.html">neuralpp::InvalidXMLException</a>, including all inherited members.<p><table>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1InvalidXMLException.html#10279e6f42a1ccb934afcfef2770c537">InvalidXMLException</a>()</td><td><a class="el" href="classneuralpp_1_1InvalidXMLException.html">neuralpp::InvalidXMLException</a></td><td><code> [inline]</code></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1InvalidXMLException.html#4a8b81678ed0c319e1715ab5ef9112da">what</a>() const </td><td><a class="el" href="classneuralpp_1_1InvalidXMLException.html">neuralpp::InvalidXMLException</a></td><td><code> [inline]</code></td></tr>
</table></div>
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<h1>neuralpp::InvalidXMLException Class Reference</h1><!-- doxytag: class="neuralpp::InvalidXMLException" -->Exception thrown when trying parsing an invalid XML.
<a href="#_details">More...</a>
<p>
<code>#include &lt;<a class="el" href="neural_09_09__exception_8hpp-source.html">neural++_exception.hpp</a>&gt;</code>
<p>
<p>
<a href="classneuralpp_1_1InvalidXMLException-members.html">List of all members.</a><table border="0" cellpadding="0" cellspacing="0">
<tr><td></td></tr>
<tr><td colspan="2"><br><h2>Public Member Functions</h2></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1InvalidXMLException.html#10279e6f42a1ccb934afcfef2770c537">InvalidXMLException</a> ()</td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">const char *&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1InvalidXMLException.html#4a8b81678ed0c319e1715ab5ef9112da">what</a> () const throw ()</td></tr>
</table>
<hr><a name="_details"></a><h2>Detailed Description</h2>
Exception thrown when trying parsing an invalid XML. <hr><h2>Constructor &amp; Destructor Documentation</h2>
<a class="anchor" name="10279e6f42a1ccb934afcfef2770c537"></a><!-- doxytag: member="neuralpp::InvalidXMLException::InvalidXMLException" ref="10279e6f42a1ccb934afcfef2770c537" args="()" -->
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<td class="memname">neuralpp::InvalidXMLException::InvalidXMLException </td>
<td>(</td>
<td class="paramname"> </td>
<td>&nbsp;)&nbsp;</td>
<td><code> [inline]</code></td>
</tr>
</table>
</div>
<div class="memdoc">
<p>
</div>
</div><p>
<hr><h2>Member Function Documentation</h2>
<a class="anchor" name="4a8b81678ed0c319e1715ab5ef9112da"></a><!-- doxytag: member="neuralpp::InvalidXMLException::what" ref="4a8b81678ed0c319e1715ab5ef9112da" args="() const " -->
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<td class="memname">const char* neuralpp::InvalidXMLException::what </td>
<td>(</td>
<td class="paramname"> </td>
<td>&nbsp;)&nbsp;</td>
<td> const throw ()<code> [inline]</code></td>
</tr>
</table>
</div>
<div class="memdoc">
<p>
</div>
</div><p>
<hr>The documentation for this class was generated from the following file:<ul>
<li><a class="el" href="neural_09_09__exception_8hpp-source.html">neural++_exception.hpp</a></ul>
</div>
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
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@ -12,6 +12,7 @@
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<li><a href="files.html"><span>Files</span></a></li>
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@ -24,18 +25,18 @@
<div class="contents">
<h1>neuralpp::Layer Member List</h1>This is the complete list of members for <a class="el" href="classneuralpp_1_1Layer.html">neuralpp::Layer</a>, including all inherited members.<p><table>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1Layer.html#824367da29f92253a027a7c5b4a4405e">actv_f</a></td><td><a class="el" href="classneuralpp_1_1Layer.html">neuralpp::Layer</a></td><td><code> [private]</code></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1Layer.html#855685c9da56b06b629e13a2f8c719ce">elements</a></td><td><a class="el" href="classneuralpp_1_1Layer.html">neuralpp::Layer</a></td><td><code> [private]</code></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1Layer.html#fb08bddd85d36570dabfe915461f07c5">Layer</a>(size_t sz, double(*a)(double))</td><td><a class="el" href="classneuralpp_1_1Layer.html">neuralpp::Layer</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1Layer.html#609ed16b8d79dc384b01ba7d16b72bd1">Layer</a>(vector&lt; Neuron &gt; &amp;neurons, double(*a)(double))</td><td><a class="el" href="classneuralpp_1_1Layer.html">neuralpp::Layer</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1Layer.html#8188cb5c264e6021cee9979b968a0305">elements</a></td><td><a class="el" href="classneuralpp_1_1Layer.html">neuralpp::Layer</a></td><td><code> [private]</code></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1Layer.html#a235767701b5e9dcf28c5e9e0d04cb0b">Layer</a>(size_t sz, double(*a)(double), double th=0.0)</td><td><a class="el" href="classneuralpp_1_1Layer.html">neuralpp::Layer</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1Layer.html#d79f684523f8a6e086b962c8eef37623">Layer</a>(std::vector&lt; Neuron &gt; &amp;neurons, double(*a)(double), double th=0.0)</td><td><a class="el" href="classneuralpp_1_1Layer.html">neuralpp::Layer</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1Layer.html#ac33444fde14633fa1ad4acb024ad150">link</a>(Layer &amp;l)</td><td><a class="el" href="classneuralpp_1_1Layer.html">neuralpp::Layer</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1Layer.html#45ff7554830558155c6fbce3b6827122">operator[]</a>(size_t i)</td><td><a class="el" href="classneuralpp_1_1Layer.html">neuralpp::Layer</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1Layer.html#fcfd306039dbaf91c9e2dcc8fc1f1ce1">propagate</a>()</td><td><a class="el" href="classneuralpp_1_1Layer.html">neuralpp::Layer</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1Layer.html#98f79281b680b1d18fd91fa5794c0899">setActv</a>(vector&lt; double &gt; &amp;v)</td><td><a class="el" href="classneuralpp_1_1Layer.html">neuralpp::Layer</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1Layer.html#dbad95f635343a2998794113d7762cf7">setProp</a>(vector&lt; double &gt; &amp;v)</td><td><a class="el" href="classneuralpp_1_1Layer.html">neuralpp::Layer</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1Layer.html#88ceffc23f02a9dc24d4355767b7cca7">setInput</a>(std::vector&lt; double &gt; v)</td><td><a class="el" href="classneuralpp_1_1Layer.html">neuralpp::Layer</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1Layer.html#7ca71ed62fbe9c1e9c0fb6a8dcaf76f0">size</a>() const </td><td><a class="el" href="classneuralpp_1_1Layer.html">neuralpp::Layer</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1Layer.html#02cf4efe1da02a7404d25375c85ed71f">threshold</a></td><td><a class="el" href="classneuralpp_1_1Layer.html">neuralpp::Layer</a></td><td><code> [private]</code></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1Layer.html#c023a15a16353d0b4f44060a159f550f">update_weights</a></td><td><a class="el" href="classneuralpp_1_1Layer.html">neuralpp::Layer</a></td><td><code> [private]</code></td></tr>
</table></div>
<hr size="1"><address style="text-align: right;"><small>Generated on Sat Aug 15 02:56:02 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<a href="http://www.doxygen.org/index.html">
<img src="doxygen.png" alt="doxygen" align="middle" border="0"></a> 1.5.6 </small></address>
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@ -12,6 +12,7 @@
<li><a href="namespaces.html"><span>Namespaces</span></a></li>
<li class="current"><a href="annotated.html"><span>Classes</span></a></li>
<li><a href="files.html"><span>Files</span></a></li>
<li><a href="examples.html"><span>Examples</span></a></li>
</ul>
</div>
<div class="tabs">
@ -34,31 +35,30 @@
<a href="classneuralpp_1_1Layer-members.html">List of all members.</a><table border="0" cellpadding="0" cellspacing="0">
<tr><td></td></tr>
<tr><td colspan="2"><br><h2>Public Member Functions</h2></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1Layer.html#fb08bddd85d36570dabfe915461f07c5">Layer</a> (size_t sz, double(*a)(double))</td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1Layer.html#a235767701b5e9dcf28c5e9e0d04cb0b">Layer</a> (size_t sz, double(*a)(double), double th=0.0)</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Constructor. <a href="#fb08bddd85d36570dabfe915461f07c5"></a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1Layer.html#609ed16b8d79dc384b01ba7d16b72bd1">Layer</a> (vector&lt; <a class="el" href="classneuralpp_1_1Neuron.html">Neuron</a> &gt; &amp;neurons, double(*a)(double))</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Constructor. <a href="#a235767701b5e9dcf28c5e9e0d04cb0b"></a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1Layer.html#d79f684523f8a6e086b962c8eef37623">Layer</a> (std::vector&lt; <a class="el" href="classneuralpp_1_1Neuron.html">Neuron</a> &gt; &amp;neurons, double(*a)(double), double th=0.0)</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Alternative constructor. <a href="#609ed16b8d79dc384b01ba7d16b72bd1"></a><br></td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Alternative constructor. <a href="#d79f684523f8a6e086b962c8eef37623"></a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="el" href="classneuralpp_1_1Neuron.html">Neuron</a> &amp;&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1Layer.html#45ff7554830558155c6fbce3b6827122">operator[]</a> (size_t i) throw (NetworkIndexOutOfBoundsException)</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Redefinition for operator []. <a href="#45ff7554830558155c6fbce3b6827122"></a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">void&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1Layer.html#ac33444fde14633fa1ad4acb024ad150">link</a> (<a class="el" href="classneuralpp_1_1Layer.html">Layer</a> &amp;l)</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">It links a layer to another. <a href="#ac33444fde14633fa1ad4acb024ad150"></a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">void&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1Layer.html#dbad95f635343a2998794113d7762cf7">setProp</a> (vector&lt; double &gt; &amp;v)</td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">void&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1Layer.html#88ceffc23f02a9dc24d4355767b7cca7">setInput</a> (std::vector&lt; double &gt; v)</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">It sets a vector of propagation values to all its neurons. <a href="#dbad95f635343a2998794113d7762cf7"></a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">void&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1Layer.html#98f79281b680b1d18fd91fa5794c0899">setActv</a> (vector&lt; double &gt; &amp;v)</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">It sets a vector of activation values to all its neurons. <a href="#98f79281b680b1d18fd91fa5794c0899"></a><br></td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Set the input values for the neurons of the layer (just use it for the input layer). <a href="#88ceffc23f02a9dc24d4355767b7cca7"></a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">void&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1Layer.html#fcfd306039dbaf91c9e2dcc8fc1f1ce1">propagate</a> ()</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">It propagates its activation values to the output layers. <a href="#fcfd306039dbaf91c9e2dcc8fc1f1ce1"></a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">size_t&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1Layer.html#7ca71ed62fbe9c1e9c0fb6a8dcaf76f0">size</a> () const </td></tr>
<tr><td colspan="2"><br><h2>Private Attributes</h2></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">vector&lt; <a class="el" href="classneuralpp_1_1Neuron.html">Neuron</a> &gt;&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1Layer.html#855685c9da56b06b629e13a2f8c719ce">elements</a></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">std::vector&lt; <a class="el" href="classneuralpp_1_1Neuron.html">Neuron</a> &gt;&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1Layer.html#8188cb5c264e6021cee9979b968a0305">elements</a></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">double&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1Layer.html#02cf4efe1da02a7404d25375c85ed71f">threshold</a></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">void(*&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1Layer.html#c023a15a16353d0b4f44060a159f550f">update_weights</a> )()</td></tr>
@ -69,7 +69,7 @@
Class for managing layers of neurons.
<p>
Don't use this class directly unless you know what you're doing, use <a class="el" href="classneuralpp_1_1NeuralNet.html" title="Main project&#39;s class.">NeuralNet</a> instead <hr><h2>Constructor &amp; Destructor Documentation</h2>
<a class="anchor" name="fb08bddd85d36570dabfe915461f07c5"></a><!-- doxytag: member="neuralpp::Layer::Layer" ref="fb08bddd85d36570dabfe915461f07c5" args="(size_t sz, double(*a)(double))" -->
<a class="anchor" name="a235767701b5e9dcf28c5e9e0d04cb0b"></a><!-- doxytag: member="neuralpp::Layer::Layer" ref="a235767701b5e9dcf28c5e9e0d04cb0b" args="(size_t sz, double(*a)(double), double th=0.0)" -->
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@ -83,7 +83,13 @@ Don't use this class directly unless you know what you're doing, use <a class="e
<td class="paramkey"></td>
<td></td>
<td class="paramtype">double(*)(double)&nbsp;</td>
<td class="paramname"> <em>a</em></td><td>&nbsp;</td>
<td class="paramname"> <em>a</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">double&nbsp;</td>
<td class="paramname"> <em>th</em> = <code>0.0</code></td><td>&nbsp;</td>
</tr>
<tr>
<td></td>
@ -101,26 +107,33 @@ Constructor.
<table border="0" cellspacing="2" cellpadding="0">
<tr><td valign="top"></td><td valign="top"><em>sz</em>&nbsp;</td><td>Size of the layer </td></tr>
<tr><td valign="top"></td><td valign="top"><em>a</em>&nbsp;</td><td>Activation function </td></tr>
<tr><td valign="top"></td><td valign="top"><em>th</em>&nbsp;</td><td>Threshold, value in [0,1] that establishes how much a neuron must be 'sensitive' on variations of the input values </td></tr>
</table>
</dl>
</div>
</div><p>
<a class="anchor" name="609ed16b8d79dc384b01ba7d16b72bd1"></a><!-- doxytag: member="neuralpp::Layer::Layer" ref="609ed16b8d79dc384b01ba7d16b72bd1" args="(vector&lt; Neuron &gt; &amp;neurons, double(*a)(double))" -->
<a class="anchor" name="d79f684523f8a6e086b962c8eef37623"></a><!-- doxytag: member="neuralpp::Layer::Layer" ref="d79f684523f8a6e086b962c8eef37623" args="(std::vector&lt; Neuron &gt; &amp;neurons, double(*a)(double), double th=0.0)" -->
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<td class="memname">neuralpp::Layer::Layer </td>
<td>(</td>
<td class="paramtype">vector&lt; <a class="el" href="classneuralpp_1_1Neuron.html">Neuron</a> &gt; &amp;&nbsp;</td>
<td class="paramtype">std::vector&lt; <a class="el" href="classneuralpp_1_1Neuron.html">Neuron</a> &gt; &amp;&nbsp;</td>
<td class="paramname"> <em>neurons</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">double(*)(double)&nbsp;</td>
<td class="paramname"> <em>a</em></td><td>&nbsp;</td>
<td class="paramname"> <em>a</em>, </td>
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<td class="paramkey"></td>
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<td class="paramtype">double&nbsp;</td>
<td class="paramname"> <em>th</em> = <code>0.0</code></td><td>&nbsp;</td>
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<td></td>
@ -138,6 +151,7 @@ It directly gets a vector of neurons to build the layer <dl compact><dt><b>Param
<table border="0" cellspacing="2" cellpadding="0">
<tr><td valign="top"></td><td valign="top"><em>neurons</em>&nbsp;</td><td>Vector of neurons to be included in the layer </td></tr>
<tr><td valign="top"></td><td valign="top"><em>a</em>&nbsp;</td><td>Activation function </td></tr>
<tr><td valign="top"></td><td valign="top"><em>th</em>&nbsp;</td><td>Threshold, value in [0,1] that establishes how much a neuron must be 'sensitive' on variations of the input values </td></tr>
</table>
</dl>
@ -154,7 +168,7 @@ It directly gets a vector of neurons to build the layer <dl compact><dt><b>Param
<td class="paramtype">size_t&nbsp;</td>
<td class="paramname"> <em>i</em> </td>
<td>&nbsp;)&nbsp;</td>
<td> throw (NetworkIndexOutOfBoundsException)</td>
<td> throw (<a class="el" href="classneuralpp_1_1NetworkIndexOutOfBoundsException.html">NetworkIndexOutOfBoundsException</a>)</td>
</tr>
</table>
</div>
@ -199,14 +213,14 @@ It links a layer to another.
</div>
</div><p>
<a class="anchor" name="dbad95f635343a2998794113d7762cf7"></a><!-- doxytag: member="neuralpp::Layer::setProp" ref="dbad95f635343a2998794113d7762cf7" args="(vector&lt; double &gt; &amp;v)" -->
<a class="anchor" name="88ceffc23f02a9dc24d4355767b7cca7"></a><!-- doxytag: member="neuralpp::Layer::setInput" ref="88ceffc23f02a9dc24d4355767b7cca7" args="(std::vector&lt; double &gt; v)" -->
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<td class="memname">void neuralpp::Layer::setProp </td>
<td class="memname">void neuralpp::Layer::setInput </td>
<td>(</td>
<td class="paramtype">vector&lt; double &gt; &amp;&nbsp;</td>
<td class="paramtype">std::vector&lt; double &gt;&nbsp;</td>
<td class="paramname"> <em>v</em> </td>
<td>&nbsp;)&nbsp;</td>
<td></td>
@ -216,38 +230,11 @@ It links a layer to another.
<div class="memdoc">
<p>
It sets a vector of propagation values to all its neurons.
Set the input values for the neurons of the layer (just use it for the input layer).
<p>
<dl compact><dt><b>Parameters:</b></dt><dd>
<table border="0" cellspacing="2" cellpadding="0">
<tr><td valign="top"></td><td valign="top"><em>v</em>&nbsp;</td><td>Vector of values to write as propagation values </td></tr>
</table>
</dl>
</div>
</div><p>
<a class="anchor" name="98f79281b680b1d18fd91fa5794c0899"></a><!-- doxytag: member="neuralpp::Layer::setActv" ref="98f79281b680b1d18fd91fa5794c0899" args="(vector&lt; double &gt; &amp;v)" -->
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<td class="memname">void neuralpp::Layer::setActv </td>
<td>(</td>
<td class="paramtype">vector&lt; double &gt; &amp;&nbsp;</td>
<td class="paramname"> <em>v</em> </td>
<td>&nbsp;)&nbsp;</td>
<td></td>
</tr>
</table>
</div>
<div class="memdoc">
<p>
It sets a vector of activation values to all its neurons.
<p>
<dl compact><dt><b>Parameters:</b></dt><dd>
<table border="0" cellspacing="2" cellpadding="0">
<tr><td valign="top"></td><td valign="top"><em>v</em>&nbsp;</td><td>Vector of values to write as activation values </td></tr>
<tr><td valign="top"></td><td valign="top"><em>v</em>&nbsp;</td><td>Vector containing the input values </td></tr>
</table>
</dl>
@ -295,12 +282,27 @@ It propagates its activation values to the output layers.
</div>
</div><p>
<hr><h2>Member Data Documentation</h2>
<a class="anchor" name="855685c9da56b06b629e13a2f8c719ce"></a><!-- doxytag: member="neuralpp::Layer::elements" ref="855685c9da56b06b629e13a2f8c719ce" args="" -->
<a class="anchor" name="8188cb5c264e6021cee9979b968a0305"></a><!-- doxytag: member="neuralpp::Layer::elements" ref="8188cb5c264e6021cee9979b968a0305" args="" -->
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<td class="memname">vector&lt;<a class="el" href="classneuralpp_1_1Neuron.html">Neuron</a>&gt; <a class="el" href="classneuralpp_1_1Layer.html#855685c9da56b06b629e13a2f8c719ce">neuralpp::Layer::elements</a><code> [private]</code> </td>
<td class="memname">std::vector&lt;<a class="el" href="classneuralpp_1_1Neuron.html">Neuron</a>&gt; <a class="el" href="classneuralpp_1_1Layer.html#8188cb5c264e6021cee9979b968a0305">neuralpp::Layer::elements</a><code> [private]</code> </td>
</tr>
</table>
</div>
<div class="memdoc">
<p>
</div>
</div><p>
<a class="anchor" name="02cf4efe1da02a7404d25375c85ed71f"></a><!-- doxytag: member="neuralpp::Layer::threshold" ref="02cf4efe1da02a7404d25375c85ed71f" args="" -->
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<td class="memname">double <a class="el" href="classneuralpp_1_1Layer.html#02cf4efe1da02a7404d25375c85ed71f">neuralpp::Layer::threshold</a><code> [private]</code> </td>
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@ -343,7 +345,7 @@ It propagates its activation values to the output layers.
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<h1>neuralpp::NetworkFileNotFoundException Member List</h1>This is the complete list of members for <a class="el" href="classneuralpp_1_1NetworkFileNotFoundException.html">neuralpp::NetworkFileNotFoundException</a>, including all inherited members.<p><table>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1NetworkFileNotFoundException.html#9603eebdb841f06c9b1007e65cba60f6">NetworkFileNotFoundException</a>()</td><td><a class="el" href="classneuralpp_1_1NetworkFileNotFoundException.html">neuralpp::NetworkFileNotFoundException</a></td><td><code> [inline]</code></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1NetworkFileNotFoundException.html#24cde7729ab22d343f36e638cfc40702">what</a>() const </td><td><a class="el" href="classneuralpp_1_1NetworkFileNotFoundException.html">neuralpp::NetworkFileNotFoundException</a></td><td><code> [inline]</code></td></tr>
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<h1>neuralpp::NetworkFileNotFoundException Class Reference</h1><!-- doxytag: class="neuralpp::NetworkFileNotFoundException" -->Exception thrown when doing an attempt to load a network from an invalid file.
<a href="#_details">More...</a>
<p>
<code>#include &lt;<a class="el" href="neural_09_09__exception_8hpp-source.html">neural++_exception.hpp</a>&gt;</code>
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<p>
<a href="classneuralpp_1_1NetworkFileNotFoundException-members.html">List of all members.</a><table border="0" cellpadding="0" cellspacing="0">
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<tr><td colspan="2"><br><h2>Public Member Functions</h2></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1NetworkFileNotFoundException.html#9603eebdb841f06c9b1007e65cba60f6">NetworkFileNotFoundException</a> ()</td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">const char *&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1NetworkFileNotFoundException.html#24cde7729ab22d343f36e638cfc40702">what</a> () const throw ()</td></tr>
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<hr><a name="_details"></a><h2>Detailed Description</h2>
Exception thrown when doing an attempt to load a network from an invalid file. <dl compact><dt><b>Examples: </b></dt><dd>
<p>
<a class="el" href="examples_2doAdd_8cpp-example.html#_a1">examples/doAdd.cpp</a>.</dl><hr><h2>Constructor &amp; Destructor Documentation</h2>
<a class="anchor" name="9603eebdb841f06c9b1007e65cba60f6"></a><!-- doxytag: member="neuralpp::NetworkFileNotFoundException::NetworkFileNotFoundException" ref="9603eebdb841f06c9b1007e65cba60f6" args="()" -->
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<td class="memname">neuralpp::NetworkFileNotFoundException::NetworkFileNotFoundException </td>
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<td><code> [inline]</code></td>
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<hr><h2>Member Function Documentation</h2>
<a class="anchor" name="24cde7729ab22d343f36e638cfc40702"></a><!-- doxytag: member="neuralpp::NetworkFileNotFoundException::what" ref="24cde7729ab22d343f36e638cfc40702" args="() const " -->
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<td class="memname">const char* neuralpp::NetworkFileNotFoundException::what </td>
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<td> const throw ()<code> [inline]</code></td>
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<dl compact><dt><b>Examples: </b></dt><dd>
<a class="el" href="examples_2doAdd_8cpp-example.html#a2">examples/doAdd.cpp</a>.</dl>
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<hr>The documentation for this class was generated from the following file:<ul>
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<h1>neuralpp::NetworkFileWriteException Member List</h1>This is the complete list of members for <a class="el" href="classneuralpp_1_1NetworkFileWriteException.html">neuralpp::NetworkFileWriteException</a>, including all inherited members.<p><table>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1NetworkFileWriteException.html#83bc897b0ea11a384e0839a39e9fdb48">NetworkFileWriteException</a>()</td><td><a class="el" href="classneuralpp_1_1NetworkFileWriteException.html">neuralpp::NetworkFileWriteException</a></td><td><code> [inline]</code></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1NetworkFileWriteException.html#c8802852cb38d5edf6f490ff3acb6078">what</a>() const </td><td><a class="el" href="classneuralpp_1_1NetworkFileWriteException.html">neuralpp::NetworkFileWriteException</a></td><td><code> [inline]</code></td></tr>
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<h1>neuralpp::NetworkFileWriteException Class Reference</h1><!-- doxytag: class="neuralpp::NetworkFileWriteException" -->Exception thrown when trying to write the network's information to a file that cannot be written.
<a href="#_details">More...</a>
<p>
<code>#include &lt;<a class="el" href="neural_09_09__exception_8hpp-source.html">neural++_exception.hpp</a>&gt;</code>
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<a href="classneuralpp_1_1NetworkFileWriteException-members.html">List of all members.</a><table border="0" cellpadding="0" cellspacing="0">
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<tr><td class="memItemLeft" nowrap align="right" valign="top">const char *&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1NetworkFileWriteException.html#c8802852cb38d5edf6f490ff3acb6078">what</a> () const throw ()</td></tr>
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<hr><a name="_details"></a><h2>Detailed Description</h2>
Exception thrown when trying to write the network's information to a file that cannot be written. <hr><h2>Constructor &amp; Destructor Documentation</h2>
<a class="anchor" name="83bc897b0ea11a384e0839a39e9fdb48"></a><!-- doxytag: member="neuralpp::NetworkFileWriteException::NetworkFileWriteException" ref="83bc897b0ea11a384e0839a39e9fdb48" args="()" -->
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<hr><h2>Member Function Documentation</h2>
<a class="anchor" name="c8802852cb38d5edf6f490ff3acb6078"></a><!-- doxytag: member="neuralpp::NetworkFileWriteException::what" ref="c8802852cb38d5edf6f490ff3acb6078" args="() const " -->
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<hr>The documentation for this class was generated from the following file:<ul>
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<h1>neuralpp::NetworkIndexOutOfBoundsException Member List</h1>This is the complete list of members for <a class="el" href="classneuralpp_1_1NetworkIndexOutOfBoundsException.html">neuralpp::NetworkIndexOutOfBoundsException</a>, including all inherited members.<p><table>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1NetworkIndexOutOfBoundsException.html#07141d2225ea9f2d486e755a3660d594">NetworkIndexOutOfBoundsException</a>()</td><td><a class="el" href="classneuralpp_1_1NetworkIndexOutOfBoundsException.html">neuralpp::NetworkIndexOutOfBoundsException</a></td><td><code> [inline]</code></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1NetworkIndexOutOfBoundsException.html#8b65d77cb375a0aa40d5a9ea692bd5c3">what</a>() const </td><td><a class="el" href="classneuralpp_1_1NetworkIndexOutOfBoundsException.html">neuralpp::NetworkIndexOutOfBoundsException</a></td><td><code> [inline]</code></td></tr>
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<h1>neuralpp::NetworkIndexOutOfBoundsException Class Reference</h1><!-- doxytag: class="neuralpp::NetworkIndexOutOfBoundsException" -->Exception raised when trying to access a neuron whose index is larger than the number of neurons in the network.
<a href="#_details">More...</a>
<p>
<code>#include &lt;<a class="el" href="neural_09_09__exception_8hpp-source.html">neural++_exception.hpp</a>&gt;</code>
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<a href="classneuralpp_1_1NetworkIndexOutOfBoundsException-members.html">List of all members.</a><table border="0" cellpadding="0" cellspacing="0">
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<tr><td class="memItemLeft" nowrap align="right" valign="top">const char *&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1NetworkIndexOutOfBoundsException.html#8b65d77cb375a0aa40d5a9ea692bd5c3">what</a> () const throw ()</td></tr>
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<hr><a name="_details"></a><h2>Detailed Description</h2>
Exception raised when trying to access a neuron whose index is larger than the number of neurons in the network. <hr><h2>Constructor &amp; Destructor Documentation</h2>
<a class="anchor" name="07141d2225ea9f2d486e755a3660d594"></a><!-- doxytag: member="neuralpp::NetworkIndexOutOfBoundsException::NetworkIndexOutOfBoundsException" ref="07141d2225ea9f2d486e755a3660d594" args="()" -->
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<hr><h2>Member Function Documentation</h2>
<a class="anchor" name="8b65d77cb375a0aa40d5a9ea692bd5c3"></a><!-- doxytag: member="neuralpp::NetworkIndexOutOfBoundsException::what" ref="8b65d77cb375a0aa40d5a9ea692bd5c3" args="() const " -->
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<td class="memname">const char* neuralpp::NetworkIndexOutOfBoundsException::what </td>
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<td> const throw ()<code> [inline]</code></td>
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<hr>The documentation for this class was generated from the following file:<ul>
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<h1>neuralpp::NeuralNet Member List</h1>This is the complete list of members for <a class="el" href="classneuralpp_1_1NeuralNet.html">neuralpp::NeuralNet</a>, including all inherited members.<p><table>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1NeuralNet.html#c1469e6afd87d85b82f14bc246f82457">actv_f</a></td><td><a class="el" href="classneuralpp_1_1NeuralNet.html">neuralpp::NeuralNet</a></td><td><code> [private]</code></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1NeuralNet.html#28b9966c5f197b8e86d57dd104aa32a6">closeXML</a>(string &amp;xml)</td><td><a class="el" href="classneuralpp_1_1NeuralNet.html">neuralpp::NeuralNet</a></td><td><code> [static]</code></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1NeuralNet.html#62695a82dfb1df758a44150921aec8e0">commitChanges</a>(Layer *l)</td><td><a class="el" href="classneuralpp_1_1NeuralNet.html">neuralpp::NeuralNet</a></td><td><code> [private]</code></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1NeuralNet.html#e17732ed578bc4bd6032bfae58a5cf51">closeXML</a>(std::string &amp;xml)</td><td><a class="el" href="classneuralpp_1_1NeuralNet.html">neuralpp::NeuralNet</a></td><td><code> [static]</code></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1NeuralNet.html#f697a8d9967ad8f03e5a16a42cd110c5">commitChanges</a>(Layer &amp;l)</td><td><a class="el" href="classneuralpp_1_1NeuralNet.html">neuralpp::NeuralNet</a></td><td><code> [private]</code></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1NeuralNet.html#4cb52dae7b43d03fac73afca7b9f3a51">epochs</a></td><td><a class="el" href="classneuralpp_1_1NeuralNet.html">neuralpp::NeuralNet</a></td><td><code> [private]</code></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1NeuralNet.html#0616c51404efaca2714e37dd7478997e">error</a>(double ex) const </td><td><a class="el" href="classneuralpp_1_1NeuralNet.html">neuralpp::NeuralNet</a></td><td><code> [private]</code></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1NeuralNet.html#261f5f68fcc5be54250cfa03945266dd">ex</a></td><td><a class="el" href="classneuralpp_1_1NeuralNet.html">neuralpp::NeuralNet</a></td><td><code> [private]</code></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1NeuralNet.html#8a140d28e6dd4097470c7c138801ad01">error</a>(double ex)</td><td><a class="el" href="classneuralpp_1_1NeuralNet.html">neuralpp::NeuralNet</a></td><td><code> [private]</code></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1NeuralNet.html#a9e4ff43427f56663739c4c7450de8ee">expect</a></td><td><a class="el" href="classneuralpp_1_1NeuralNet.html">neuralpp::NeuralNet</a></td><td><code> [private]</code></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1NeuralNet.html#562dfe9fb8d73bf25a23ce608451d3aa">expected</a>() const </td><td><a class="el" href="classneuralpp_1_1NeuralNet.html">neuralpp::NeuralNet</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1NeuralNet.html#94c36c94060e785ea67a0014c4182f8f5ec2727c0756ddb097b53efe49b81afb">file</a> enum value</td><td><a class="el" href="classneuralpp_1_1NeuralNet.html">neuralpp::NeuralNet</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1NeuralNet.html#51a1851ed07b85bec091c9053ae99cf7">getExpected</a>() const </td><td><a class="el" href="classneuralpp_1_1NeuralNet.html">neuralpp::NeuralNet</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1NeuralNet.html#961dce8913264bf64c899dce4e25f810">getOutput</a>() const </td><td><a class="el" href="classneuralpp_1_1NeuralNet.html">neuralpp::NeuralNet</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1NeuralNet.html#a6b8bf3800b43b58843c65fc431207ae">getOutputs</a>()</td><td><a class="el" href="classneuralpp_1_1NeuralNet.html">neuralpp::NeuralNet</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1NeuralNet.html#e6d2215ecc8b560db2f6797db642191c">getOutputs</a>()</td><td><a class="el" href="classneuralpp_1_1NeuralNet.html">neuralpp::NeuralNet</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1NeuralNet.html#e08cdcf4b70f987700e553d9914f6179">getThreshold</a>() const </td><td><a class="el" href="classneuralpp_1_1NeuralNet.html">neuralpp::NeuralNet</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1NeuralNet.html#bbdaa1b6c0a1a95d2b18cd25fda2a266">hidden</a></td><td><a class="el" href="classneuralpp_1_1NeuralNet.html">neuralpp::NeuralNet</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1NeuralNet.html#45c7645d4affe65752d37cd230afba24">initXML</a>(string &amp;xml)</td><td><a class="el" href="classneuralpp_1_1NeuralNet.html">neuralpp::NeuralNet</a></td><td><code> [static]</code></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1NeuralNet.html#96da6712a72051cf34ad961761ef6e08">initXML</a>(std::string &amp;xml)</td><td><a class="el" href="classneuralpp_1_1NeuralNet.html">neuralpp::NeuralNet</a></td><td><code> [static]</code></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1NeuralNet.html#e2b4e8405f9d25edab395d61502bdba9">input</a></td><td><a class="el" href="classneuralpp_1_1NeuralNet.html">neuralpp::NeuralNet</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1NeuralNet.html#6bd7be443e46b2fdbf1da2edb8e611ab">l_rate</a></td><td><a class="el" href="classneuralpp_1_1NeuralNet.html">neuralpp::NeuralNet</a></td><td><code> [private]</code></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1NeuralNet.html#46f23f462318a4ffc037a4e806364c3f">link</a>()</td><td><a class="el" href="classneuralpp_1_1NeuralNet.html">neuralpp::NeuralNet</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1NeuralNet.html#92b145f2f6f00bf1ba645ce2235882c2">NeuralNet</a>()</td><td><a class="el" href="classneuralpp_1_1NeuralNet.html">neuralpp::NeuralNet</a></td><td><code> [inline]</code></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1NeuralNet.html#c79534c7c0dfb20d1d03be2ad7569b78">NeuralNet</a>(size_t in_size, size_t hidden_size, size_t out_size, double l, int e)</td><td><a class="el" href="classneuralpp_1_1NeuralNet.html">neuralpp::NeuralNet</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1NeuralNet.html#7fc7fc3e3220c138ffa5356fef6b9757">NeuralNet</a>(const string file)</td><td><a class="el" href="classneuralpp_1_1NeuralNet.html">neuralpp::NeuralNet</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1NeuralNet.html#0c16df2e0701503052c63749930b238e">NeuralNet</a>(size_t in_size, size_t hidden_size, size_t out_size, double(*actv)(double), double l, int e)</td><td><a class="el" href="classneuralpp_1_1NeuralNet.html">neuralpp::NeuralNet</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1NeuralNet.html#3d602f3988a9a3e2c77dc6955674f412">NeuralNet</a>(size_t in_size, size_t hidden_size, size_t out_size, double l, int e, double th=0.0, double(*a)(double)=__actv)</td><td><a class="el" href="classneuralpp_1_1NeuralNet.html">neuralpp::NeuralNet</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1NeuralNet.html#b4bfa407d28bb17abf7f735a049987d9">NeuralNet</a>(const std::string file)</td><td><a class="el" href="classneuralpp_1_1NeuralNet.html">neuralpp::NeuralNet</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1NeuralNet.html#fa9b2dbcbb39d0fc70f790ac24069a74">output</a></td><td><a class="el" href="classneuralpp_1_1NeuralNet.html">neuralpp::NeuralNet</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1NeuralNet.html#c129c180647362da963758bfd1ba6890">propagate</a>()</td><td><a class="el" href="classneuralpp_1_1NeuralNet.html">neuralpp::NeuralNet</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1NeuralNet.html#4f88106c9e542c39eac43b4ca1974a2a">ref_epochs</a></td><td><a class="el" href="classneuralpp_1_1NeuralNet.html">neuralpp::NeuralNet</a></td><td><code> [private]</code></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1NeuralNet.html#fdf94c276720c25e565cac834fe8a407">save</a>(const char *fname)</td><td><a class="el" href="classneuralpp_1_1NeuralNet.html">neuralpp::NeuralNet</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1NeuralNet.html#b6475762b7e9eab086befdc511f7c236">setExpected</a>(double ex)</td><td><a class="el" href="classneuralpp_1_1NeuralNet.html">neuralpp::NeuralNet</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1NeuralNet.html#0de170e8ab561ad63d0739b4c4b74f68">setInput</a>(vector&lt; double &gt; &amp;v)</td><td><a class="el" href="classneuralpp_1_1NeuralNet.html">neuralpp::NeuralNet</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1NeuralNet.html#e649edc3d86bec7c0e178d5c892b4fd7">setExpected</a>(std::vector&lt; double &gt; ex)</td><td><a class="el" href="classneuralpp_1_1NeuralNet.html">neuralpp::NeuralNet</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1NeuralNet.html#405b32d2928344314ecf0469070b0f17">setInput</a>(std::vector&lt; double &gt; v)</td><td><a class="el" href="classneuralpp_1_1NeuralNet.html">neuralpp::NeuralNet</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1NeuralNet.html#94c36c94060e785ea67a0014c4182f8f">source</a> enum name</td><td><a class="el" href="classneuralpp_1_1NeuralNet.html">neuralpp::NeuralNet</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1NeuralNet.html#e07af23ceb8666518da0c035bf1e0376">split</a>(char delim, string str)</td><td><a class="el" href="classneuralpp_1_1NeuralNet.html">neuralpp::NeuralNet</a></td><td><code> [static]</code></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1NeuralNet.html#83c6555520856d5867752904349ab6ca">split</a>(char delim, std::string str)</td><td><a class="el" href="classneuralpp_1_1NeuralNet.html">neuralpp::NeuralNet</a></td><td><code> [static]</code></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1NeuralNet.html#94c36c94060e785ea67a0014c4182f8f6d06b4fe9414a158c97aee1a3679a904">str</a> enum value</td><td><a class="el" href="classneuralpp_1_1NeuralNet.html">neuralpp::NeuralNet</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1NeuralNet.html#ead4bdef0602a5cadbe3beb685e01f5f">train</a>(string xml, source src)</td><td><a class="el" href="classneuralpp_1_1NeuralNet.html">neuralpp::NeuralNet</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1NeuralNet.html#327dbfdd72b0a74293f8f29630525aa3">threshold</a></td><td><a class="el" href="classneuralpp_1_1NeuralNet.html">neuralpp::NeuralNet</a></td><td><code> [private]</code></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1NeuralNet.html#1c9e17437d41a7048611e21a3cc1c7dd">train</a>(std::string xml, source src)</td><td><a class="el" href="classneuralpp_1_1NeuralNet.html">neuralpp::NeuralNet</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1NeuralNet.html#b0bd1daadb06980dff1f50d33a7c098e">update</a>()</td><td><a class="el" href="classneuralpp_1_1NeuralNet.html">neuralpp::NeuralNet</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1NeuralNet.html#94169c89a7cd47122ab5dbf1d5c5e108">updateWeights</a>()</td><td><a class="el" href="classneuralpp_1_1NeuralNet.html">neuralpp::NeuralNet</a></td><td><code> [private]</code></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1NeuralNet.html#4be31ecb0b543a192997bd83c6995ccb">XMLFromSet</a>(int id, string set)</td><td><a class="el" href="classneuralpp_1_1NeuralNet.html">neuralpp::NeuralNet</a></td><td><code> [static]</code></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1NeuralNet.html#0a2733037af912b3e6a10146e7b7172f">XMLFromSet</a>(int &amp;id, std::string set)</td><td><a class="el" href="classneuralpp_1_1NeuralNet.html">neuralpp::NeuralNet</a></td><td><code> [static]</code></td></tr>
</table></div>
<hr size="1"><address style="text-align: right;"><small>Generated on Sat Aug 15 02:56:02 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
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@ -43,58 +44,64 @@
<tr><td class="memItemLeft" nowrap align="right" valign="top">&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1NeuralNet.html#92b145f2f6f00bf1ba645ce2235882c2">NeuralNet</a> ()</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Empty constructor for the class - it just makes nothing. <a href="#92b145f2f6f00bf1ba645ce2235882c2"></a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1NeuralNet.html#c79534c7c0dfb20d1d03be2ad7569b78">NeuralNet</a> (size_t in_size, size_t hidden_size, size_t out_size, double l, int e)</td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1NeuralNet.html#3d602f3988a9a3e2c77dc6955674f412">NeuralNet</a> (size_t in_size, size_t hidden_size, size_t out_size, double l, int e, double th=0.0, double(*a)(double)=__actv)</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Constructor. <a href="#c79534c7c0dfb20d1d03be2ad7569b78"></a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1NeuralNet.html#7fc7fc3e3220c138ffa5356fef6b9757">NeuralNet</a> (const string file) throw (NetworkFileNotFoundException)</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Constructor. <a href="#3d602f3988a9a3e2c77dc6955674f412"></a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1NeuralNet.html#b4bfa407d28bb17abf7f735a049987d9">NeuralNet</a> (const std::string file) throw (NetworkFileNotFoundException)</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Constructor. <a href="#7fc7fc3e3220c138ffa5356fef6b9757"></a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1NeuralNet.html#0c16df2e0701503052c63749930b238e">NeuralNet</a> (size_t in_size, size_t hidden_size, size_t out_size, double(*actv)(double), double l, int e)</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Constructor. <a href="#0c16df2e0701503052c63749930b238e"></a><br></td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Constructor. <a href="#b4bfa407d28bb17abf7f735a049987d9"></a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">double&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1NeuralNet.html#961dce8913264bf64c899dce4e25f810">getOutput</a> () const </td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">It gets the output of the network (note: the layer output should contain an only neuron). <a href="#961dce8913264bf64c899dce4e25f810"></a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">vector&lt; double &gt;&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1NeuralNet.html#a6b8bf3800b43b58843c65fc431207ae">getOutputs</a> ()</td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">double&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1NeuralNet.html#e08cdcf4b70f987700e553d9914f6179">getThreshold</a> () const </td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">It gets the output of the network in case the output layer contains more neurons. <a href="#a6b8bf3800b43b58843c65fc431207ae"></a><br></td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Get the threshold of the neurons in the network. <a href="#e08cdcf4b70f987700e553d9914f6179"></a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">std::vector&lt; double &gt;&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1NeuralNet.html#e6d2215ecc8b560db2f6797db642191c">getOutputs</a> ()</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">It gets the output of the network in case the output layer contains more neurons. <a href="#e6d2215ecc8b560db2f6797db642191c"></a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">double&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1NeuralNet.html#562dfe9fb8d73bf25a23ce608451d3aa">expected</a> () const </td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">It gets the value expected. <a href="#562dfe9fb8d73bf25a23ce608451d3aa"></a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">void&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1NeuralNet.html#b6475762b7e9eab086befdc511f7c236">setExpected</a> (double <a class="el" href="classneuralpp_1_1NeuralNet.html#261f5f68fcc5be54250cfa03945266dd">ex</a>)</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Get the expected value (in case you have an only neuron in output layer). <a href="#562dfe9fb8d73bf25a23ce608451d3aa"></a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">std::vector&lt; double &gt;&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1NeuralNet.html#51a1851ed07b85bec091c9053ae99cf7">getExpected</a> () const </td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">It sets the value you expect from your network. <a href="#b6475762b7e9eab086befdc511f7c236"></a><br></td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Get the expected value (in case you have an only neuron in output layer). <a href="#51a1851ed07b85bec091c9053ae99cf7"></a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">void&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1NeuralNet.html#b6475762b7e9eab086befdc511f7c236">setExpected</a> (double ex)</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">It sets the value you expect from your network (in case the network has an only neuron in its output layer). <a href="#b6475762b7e9eab086befdc511f7c236"></a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">void&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1NeuralNet.html#e649edc3d86bec7c0e178d5c892b4fd7">setExpected</a> (std::vector&lt; double &gt; ex)</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Set the values you expect from your network. <a href="#e649edc3d86bec7c0e178d5c892b4fd7"></a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">void&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1NeuralNet.html#b0bd1daadb06980dff1f50d33a7c098e">update</a> ()</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">It updates through back-propagation the weights of the synapsis and computes again the output value for <em>epochs</em> times, calling back updateWeights and commitChanges functions. <a href="#b0bd1daadb06980dff1f50d33a7c098e"></a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">void&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1NeuralNet.html#c129c180647362da963758bfd1ba6890">propagate</a> ()</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">It propagates values through the network. <a href="#c129c180647362da963758bfd1ba6890"></a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">void&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1NeuralNet.html#0de170e8ab561ad63d0739b4c4b74f68">setInput</a> (vector&lt; double &gt; &amp;v)</td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">void&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1NeuralNet.html#405b32d2928344314ecf0469070b0f17">setInput</a> (std::vector&lt; double &gt; v)</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">It sets the input for the network. <a href="#0de170e8ab561ad63d0739b4c4b74f68"></a><br></td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">It sets the input for the network. <a href="#405b32d2928344314ecf0469070b0f17"></a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">void&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1NeuralNet.html#46f23f462318a4ffc037a4e806364c3f">link</a> ()</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">It links the layers of the network (input, hidden, output). <a href="#46f23f462318a4ffc037a4e806364c3f"></a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">void&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1NeuralNet.html#fdf94c276720c25e565cac834fe8a407">save</a> (const char *fname) throw (NetworkFileWriteException)</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Save a trained neural network to a binary file. <a href="#fdf94c276720c25e565cac834fe8a407"></a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">void&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1NeuralNet.html#ead4bdef0602a5cadbe3beb685e01f5f">train</a> (string xml, <a class="el" href="classneuralpp_1_1NeuralNet.html#94c36c94060e785ea67a0014c4182f8f">source</a> src) throw (InvalidXMLException)</td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">void&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1NeuralNet.html#1c9e17437d41a7048611e21a3cc1c7dd">train</a> (std::string xml, <a class="el" href="classneuralpp_1_1NeuralNet.html#94c36c94060e785ea67a0014c4182f8f">source</a> src) throw (InvalidXMLException)</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Train a network using a training set loaded from an XML file. <a href="#ead4bdef0602a5cadbe3beb685e01f5f"></a><br></td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Train a network using a training set loaded from an XML file. <a href="#1c9e17437d41a7048611e21a3cc1c7dd"></a><br></td></tr>
<tr><td colspan="2"><br><h2>Static Public Member Functions</h2></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">static void&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1NeuralNet.html#45c7645d4affe65752d37cd230afba24">initXML</a> (string &amp;xml)</td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">static void&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1NeuralNet.html#96da6712a72051cf34ad961761ef6e08">initXML</a> (std::string &amp;xml)</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Initialize the training XML for the neural network. <a href="#45c7645d4affe65752d37cd230afba24"></a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">static vector&lt; double &gt;&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1NeuralNet.html#e07af23ceb8666518da0c035bf1e0376">split</a> (char delim, string str)</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Initialize the training XML for the neural network. <a href="#96da6712a72051cf34ad961761ef6e08"></a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">static std::vector&lt; double &gt;&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1NeuralNet.html#83c6555520856d5867752904349ab6ca">split</a> (char delim, std::string str)</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Splits a string into a vector of doubles, given a delimitator. <a href="#e07af23ceb8666518da0c035bf1e0376"></a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">static string&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1NeuralNet.html#4be31ecb0b543a192997bd83c6995ccb">XMLFromSet</a> (int id, string set)</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Splits a string into a vector of doubles, given a delimitator. <a href="#83c6555520856d5867752904349ab6ca"></a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">static std::string&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1NeuralNet.html#0a2733037af912b3e6a10146e7b7172f">XMLFromSet</a> (int &amp;id, std::string set)</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Get a training set from a string and copies it to an XML For example, these strings could be training sets for making sums: "2,3;5" - "5,6;11" - "2,2;4" - "4,5:9" This method called on the first string will return an XML such this: '&lt;training id="0"&gt;&lt;input id="0"&gt;2&lt;/input&gt;&lt;input id="1"&gt;3&lt;/input&gt;&lt;output id="0"&gt;5&lt;/output&gt; &amp;lt/training&gt;'. <a href="#4be31ecb0b543a192997bd83c6995ccb"></a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">static void&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1NeuralNet.html#28b9966c5f197b8e86d57dd104aa32a6">closeXML</a> (string &amp;xml)</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Get a training set from a string and copies it to an XML For example, these strings could be training sets for making sums: "2,3;5" - "5,6;11" - "2,2;4" - "4,5:9" This method called on the first string will return an XML such this: '&lt;training id="0"&gt;&lt;input id="0"&gt;2&lt;/input&gt;&lt;input id="1"&gt;3&lt;/input&gt;&lt;output id="0"&gt;5&lt;/output&gt; &amp;lt/training&gt;'. <a href="#0a2733037af912b3e6a10146e7b7172f"></a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">static void&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1NeuralNet.html#e17732ed578bc4bd6032bfae58a5cf51">closeXML</a> (std::string &amp;xml)</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Closes an open XML document generated by "initXML" and "XMLFromSet". <a href="#28b9966c5f197b8e86d57dd104aa32a6"></a><br></td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Closes an open XML document generated by "initXML" and "XMLFromSet". <a href="#e17732ed578bc4bd6032bfae58a5cf51"></a><br></td></tr>
<tr><td colspan="2"><br><h2>Public Attributes</h2></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="el" href="classneuralpp_1_1Layer.html">Layer</a> *&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1NeuralNet.html#e2b4e8405f9d25edab395d61502bdba9">input</a></td></tr>
@ -106,12 +113,12 @@
<tr><td class="memItemLeft" nowrap align="right" valign="top">void&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1NeuralNet.html#94169c89a7cd47122ab5dbf1d5c5e108">updateWeights</a> ()</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">It updates the weights of the net's synapsis through back-propagation. <a href="#94169c89a7cd47122ab5dbf1d5c5e108"></a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">void&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1NeuralNet.html#62695a82dfb1df758a44150921aec8e0">commitChanges</a> (<a class="el" href="classneuralpp_1_1Layer.html">Layer</a> *l)</td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">void&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1NeuralNet.html#f697a8d9967ad8f03e5a16a42cd110c5">commitChanges</a> (<a class="el" href="classneuralpp_1_1Layer.html">Layer</a> &amp;l)</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">It commits the changes made by <a class="el" href="classneuralpp_1_1NeuralNet.html#94169c89a7cd47122ab5dbf1d5c5e108" title="It updates the weights of the net&#39;s synapsis through back-propagation.">updateWeights()</a> to the layer l. <a href="#62695a82dfb1df758a44150921aec8e0"></a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">double&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1NeuralNet.html#0616c51404efaca2714e37dd7478997e">error</a> (double <a class="el" href="classneuralpp_1_1NeuralNet.html#261f5f68fcc5be54250cfa03945266dd">ex</a>) const </td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">It commits the changes made by <a class="el" href="classneuralpp_1_1NeuralNet.html#94169c89a7cd47122ab5dbf1d5c5e108" title="It updates the weights of the net&#39;s synapsis through back-propagation.">updateWeights()</a> to the layer l. <a href="#f697a8d9967ad8f03e5a16a42cd110c5"></a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">double&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1NeuralNet.html#8a140d28e6dd4097470c7c138801ad01">error</a> (double ex)</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Get the error made on the expected result as |v-v'|/v. <a href="#0616c51404efaca2714e37dd7478997e"></a><br></td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Get the error made on the expected result as squared deviance. <a href="#8a140d28e6dd4097470c7c138801ad01"></a><br></td></tr>
<tr><td colspan="2"><br><h2>Private Attributes</h2></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">int&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1NeuralNet.html#4cb52dae7b43d03fac73afca7b9f3a51">epochs</a></td></tr>
@ -119,7 +126,9 @@
<tr><td class="memItemLeft" nowrap align="right" valign="top">double&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1NeuralNet.html#6bd7be443e46b2fdbf1da2edb8e611ab">l_rate</a></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">double&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1NeuralNet.html#261f5f68fcc5be54250cfa03945266dd">ex</a></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">double&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1NeuralNet.html#327dbfdd72b0a74293f8f29630525aa3">threshold</a></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">std::vector&lt; double &gt;&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1NeuralNet.html#a9e4ff43427f56663739c4c7450de8ee">expect</a></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">double(*&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1NeuralNet.html#c1469e6afd87d85b82f14bc246f82457">actv_f</a> )(double)</td></tr>
@ -128,7 +137,10 @@
<hr><a name="_details"></a><h2>Detailed Description</h2>
Main project's class.
<p>
Use *ONLY* this class, unless you know what you're doing <hr><h2>Member Enumeration Documentation</h2>
Use *ONLY* this class, unless you know what you're doing <dl compact><dt><b>Examples: </b></dt><dd>
<p>
<a class="el" href="examples_2adderFromScratch_8cpp-example.html#_a0">examples/adderFromScratch.cpp</a>, <a class="el" href="examples_2doAdd_8cpp-example.html#_a0">examples/doAdd.cpp</a>, and <a class="el" href="examples_2learnAdd_8cpp-example.html#_a0">examples/learnAdd.cpp</a>.</dl><hr><h2>Member Enumeration Documentation</h2>
<a class="anchor" name="94c36c94060e785ea67a0014c4182f8f"></a><!-- doxytag: member="neuralpp::NeuralNet::source" ref="94c36c94060e785ea67a0014c4182f8f" args="" -->
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@ -176,7 +188,7 @@ Empty constructor for the class - it just makes nothing.
</div>
</div><p>
<a class="anchor" name="c79534c7c0dfb20d1d03be2ad7569b78"></a><!-- doxytag: member="neuralpp::NeuralNet::NeuralNet" ref="c79534c7c0dfb20d1d03be2ad7569b78" args="(size_t in_size, size_t hidden_size, size_t out_size, double l, int e)" -->
<a class="anchor" name="3d602f3988a9a3e2c77dc6955674f412"></a><!-- doxytag: member="neuralpp::NeuralNet::NeuralNet" ref="3d602f3988a9a3e2c77dc6955674f412" args="(size_t in_size, size_t hidden_size, size_t out_size, double l, int e, double th=0.0, double(*a)(double)=__actv)" -->
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@ -208,7 +220,19 @@ Empty constructor for the class - it just makes nothing.
<td class="paramkey"></td>
<td></td>
<td class="paramtype">int&nbsp;</td>
<td class="paramname"> <em>e</em></td><td>&nbsp;</td>
<td class="paramname"> <em>e</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">double&nbsp;</td>
<td class="paramname"> <em>th</em> = <code>0.0</code>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">double(*)(double)&nbsp;</td>
<td class="paramname"> <em>a</em> = <code>__actv</code></td><td>&nbsp;</td>
</tr>
<tr>
<td></td>
@ -229,22 +253,24 @@ Constructor.
<tr><td valign="top"></td><td valign="top"><em>out_size</em>&nbsp;</td><td>Size of the output layer </td></tr>
<tr><td valign="top"></td><td valign="top"><em>l</em>&nbsp;</td><td>learn rate (get it after doing some experiments, but generally try to keep its value quite low to be more accurate) </td></tr>
<tr><td valign="top"></td><td valign="top"><em>e</em>&nbsp;</td><td>Epochs (cycles) to execute (the most you execute, the most the network can be accurate for its purpose) </td></tr>
<tr><td valign="top"></td><td valign="top"><em>th</em>&nbsp;</td><td>Threshold, value in [0,1] that establishes how much a neuron must be 'sensitive' on variations of the input values </td></tr>
<tr><td valign="top"></td><td valign="top"><em>a</em>&nbsp;</td><td>Activation function to use (default: f(x)=x) </td></tr>
</table>
</dl>
</div>
</div><p>
<a class="anchor" name="7fc7fc3e3220c138ffa5356fef6b9757"></a><!-- doxytag: member="neuralpp::NeuralNet::NeuralNet" ref="7fc7fc3e3220c138ffa5356fef6b9757" args="(const string file)" -->
<a class="anchor" name="b4bfa407d28bb17abf7f735a049987d9"></a><!-- doxytag: member="neuralpp::NeuralNet::NeuralNet" ref="b4bfa407d28bb17abf7f735a049987d9" args="(const std::string file)" -->
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<td class="memname">neuralpp::NeuralNet::NeuralNet </td>
<td>(</td>
<td class="paramtype">const string&nbsp;</td>
<td class="paramtype">const std::string&nbsp;</td>
<td class="paramname"> <em>file</em> </td>
<td>&nbsp;)&nbsp;</td>
<td> throw (NetworkFileNotFoundException)</td>
<td> throw (<a class="el" href="classneuralpp_1_1NetworkFileNotFoundException.html">NetworkFileNotFoundException</a>)</td>
</tr>
</table>
</div>
@ -260,72 +286,7 @@ Constructor.
</dl>
<dl compact><dt><b>Exceptions:</b></dt><dd>
<table border="0" cellspacing="2" cellpadding="0">
<tr><td valign="top"></td><td valign="top"><em>NetworkFileNotFoundException</em>&nbsp;</td><td></td></tr>
</table>
</dl>
</div>
</div><p>
<a class="anchor" name="0c16df2e0701503052c63749930b238e"></a><!-- doxytag: member="neuralpp::NeuralNet::NeuralNet" ref="0c16df2e0701503052c63749930b238e" args="(size_t in_size, size_t hidden_size, size_t out_size, double(*actv)(double), double l, int e)" -->
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<td class="memname">neuralpp::NeuralNet::NeuralNet </td>
<td>(</td>
<td class="paramtype">size_t&nbsp;</td>
<td class="paramname"> <em>in_size</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">size_t&nbsp;</td>
<td class="paramname"> <em>hidden_size</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">size_t&nbsp;</td>
<td class="paramname"> <em>out_size</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">double(*)(double)&nbsp;</td>
<td class="paramname"> <em>actv</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">double&nbsp;</td>
<td class="paramname"> <em>l</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">int&nbsp;</td>
<td class="paramname"> <em>e</em></td><td>&nbsp;</td>
</tr>
<tr>
<td></td>
<td>)</td>
<td></td><td></td><td></td>
</tr>
</table>
</div>
<div class="memdoc">
<p>
Constructor.
<p>
<dl compact><dt><b>Parameters:</b></dt><dd>
<table border="0" cellspacing="2" cellpadding="0">
<tr><td valign="top"></td><td valign="top"><em>in_size</em>&nbsp;</td><td>Size of the input layer </td></tr>
<tr><td valign="top"></td><td valign="top"><em>hidden_size</em>&nbsp;</td><td>Size of the hidden layer </td></tr>
<tr><td valign="top"></td><td valign="top"><em>out_size</em>&nbsp;</td><td>Size of the output layer </td></tr>
<tr><td valign="top"></td><td valign="top"><em>actv</em>&nbsp;</td><td>Activation function to use (default: f(x)=x) </td></tr>
<tr><td valign="top"></td><td valign="top"><em>l</em>&nbsp;</td><td>learn rate (get it after doing some experiments, but generally try to keep its value quite low to be more accurate) </td></tr>
<tr><td valign="top"></td><td valign="top"><em>e</em>&nbsp;</td><td>Epochs (cycles) to execute (the most you execute, the most the network can be accurate for its purpose) </td></tr>
<tr><td valign="top"></td><td valign="top"><em><a class="el" href="classneuralpp_1_1NetworkFileNotFoundException.html" title="Exception thrown when doing an attempt to load a network from an invalid file.">NetworkFileNotFoundException</a></em>&nbsp;</td><td></td></tr>
</table>
</dl>
@ -353,14 +314,14 @@ It updates the weights of the net's synapsis through back-propagation.
In-class use only
</div>
</div><p>
<a class="anchor" name="62695a82dfb1df758a44150921aec8e0"></a><!-- doxytag: member="neuralpp::NeuralNet::commitChanges" ref="62695a82dfb1df758a44150921aec8e0" args="(Layer *l)" -->
<a class="anchor" name="f697a8d9967ad8f03e5a16a42cd110c5"></a><!-- doxytag: member="neuralpp::NeuralNet::commitChanges" ref="f697a8d9967ad8f03e5a16a42cd110c5" args="(Layer &amp;l)" -->
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<td class="memname">void neuralpp::NeuralNet::commitChanges </td>
<td>(</td>
<td class="paramtype"><a class="el" href="classneuralpp_1_1Layer.html">Layer</a> *&nbsp;</td>
<td class="paramtype"><a class="el" href="classneuralpp_1_1Layer.html">Layer</a> &amp;&nbsp;</td>
<td class="paramname"> <em>l</em> </td>
<td>&nbsp;)&nbsp;</td>
<td><code> [private]</code></td>
@ -380,7 +341,7 @@ In-class use only <dl compact><dt><b>Parameters:</b></dt><dd>
</div>
</div><p>
<a class="anchor" name="0616c51404efaca2714e37dd7478997e"></a><!-- doxytag: member="neuralpp::NeuralNet::error" ref="0616c51404efaca2714e37dd7478997e" args="(double ex) const " -->
<a class="anchor" name="8a140d28e6dd4097470c7c138801ad01"></a><!-- doxytag: member="neuralpp::NeuralNet::error" ref="8a140d28e6dd4097470c7c138801ad01" args="(double ex)" -->
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@ -390,14 +351,14 @@ In-class use only <dl compact><dt><b>Parameters:</b></dt><dd>
<td class="paramtype">double&nbsp;</td>
<td class="paramname"> <em>ex</em> </td>
<td>&nbsp;)&nbsp;</td>
<td> const<code> [private]</code></td>
<td><code> [private]</code></td>
</tr>
</table>
</div>
<div class="memdoc">
<p>
Get the error made on the expected result as |v-v'|/v.
Get the error made on the expected result as squared deviance.
<p>
<dl compact><dt><b>Parameters:</b></dt><dd>
<table border="0" cellspacing="2" cellpadding="0">
@ -427,15 +388,38 @@ Get the error made on the expected result as |v-v'|/v.
It gets the output of the network (note: the layer output should contain an only neuron).
<p>
<dl class="return" compact><dt><b>Returns:</b></dt><dd>The output value of the network </dd></dl>
<dl compact><dt><b>Examples: </b></dt><dd>
<a class="el" href="examples_2doAdd_8cpp-example.html#a5">examples/doAdd.cpp</a>.</dl>
</div>
</div><p>
<a class="anchor" name="a6b8bf3800b43b58843c65fc431207ae"></a><!-- doxytag: member="neuralpp::NeuralNet::getOutputs" ref="a6b8bf3800b43b58843c65fc431207ae" args="()" -->
<a class="anchor" name="e08cdcf4b70f987700e553d9914f6179"></a><!-- doxytag: member="neuralpp::NeuralNet::getThreshold" ref="e08cdcf4b70f987700e553d9914f6179" args="() const " -->
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<td class="memname">vector&lt;double&gt; neuralpp::NeuralNet::getOutputs </td>
<td class="memname">double neuralpp::NeuralNet::getThreshold </td>
<td>(</td>
<td class="paramname"> </td>
<td>&nbsp;)&nbsp;</td>
<td> const</td>
</tr>
</table>
</div>
<div class="memdoc">
<p>
Get the threshold of the neurons in the network.
<p>
<dl class="return" compact><dt><b>Returns:</b></dt><dd>The threshold of the neurons </dd></dl>
</div>
</div><p>
<a class="anchor" name="e6d2215ecc8b560db2f6797db642191c"></a><!-- doxytag: member="neuralpp::NeuralNet::getOutputs" ref="e6d2215ecc8b560db2f6797db642191c" args="()" -->
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<td class="memname">std::vector&lt;double&gt; neuralpp::NeuralNet::getOutputs </td>
<td>(</td>
<td class="paramname"> </td>
<td>&nbsp;)&nbsp;</td>
@ -449,7 +433,8 @@ It gets the output of the network (note: the layer output should contain an only
It gets the output of the network in case the output layer contains more neurons.
<p>
<dl class="return" compact><dt><b>Returns:</b></dt><dd>A vector containing the output values of the network </dd></dl>
<dl compact><dt><b>Examples: </b></dt><dd>
<a class="el" href="examples_2adderFromScratch_8cpp-example.html#a4">examples/adderFromScratch.cpp</a>.</dl>
</div>
</div><p>
<a class="anchor" name="562dfe9fb8d73bf25a23ce608451d3aa"></a><!-- doxytag: member="neuralpp::NeuralNet::expected" ref="562dfe9fb8d73bf25a23ce608451d3aa" args="() const " -->
@ -468,7 +453,29 @@ It gets the output of the network in case the output layer contains more neurons
<div class="memdoc">
<p>
It gets the value expected.
Get the expected value (in case you have an only neuron in output layer).
<p>
Of course you should specify this when you build your network by using setExpected. <dl class="return" compact><dt><b>Returns:</b></dt><dd>The expected output value for a certain training phase </dd></dl>
</div>
</div><p>
<a class="anchor" name="51a1851ed07b85bec091c9053ae99cf7"></a><!-- doxytag: member="neuralpp::NeuralNet::getExpected" ref="51a1851ed07b85bec091c9053ae99cf7" args="() const " -->
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<td class="memname">std::vector&lt;double&gt; neuralpp::NeuralNet::getExpected </td>
<td>(</td>
<td class="paramname"> </td>
<td>&nbsp;)&nbsp;</td>
<td> const</td>
</tr>
</table>
</div>
<div class="memdoc">
<p>
Get the expected value (in case you have an only neuron in output layer).
<p>
Of course you should specify this when you build your network by using setExpected. <dl class="return" compact><dt><b>Returns:</b></dt><dd>The expected output value for a certain training phase </dd></dl>
@ -491,7 +498,7 @@ Of course you should specify this when you build your network by using setExpect
<div class="memdoc">
<p>
It sets the value you expect from your network.
It sets the value you expect from your network (in case the network has an only neuron in its output layer).
<p>
<dl compact><dt><b>Parameters:</b></dt><dd>
<table border="0" cellspacing="2" cellpadding="0">
@ -499,6 +506,33 @@ It sets the value you expect from your network.
</table>
</dl>
</div>
</div><p>
<a class="anchor" name="e649edc3d86bec7c0e178d5c892b4fd7"></a><!-- doxytag: member="neuralpp::NeuralNet::setExpected" ref="e649edc3d86bec7c0e178d5c892b4fd7" args="(std::vector&lt; double &gt; ex)" -->
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<td class="memname">void neuralpp::NeuralNet::setExpected </td>
<td>(</td>
<td class="paramtype">std::vector&lt; double &gt;&nbsp;</td>
<td class="paramname"> <em>ex</em> </td>
<td>&nbsp;)&nbsp;</td>
<td></td>
</tr>
</table>
</div>
<div class="memdoc">
<p>
Set the values you expect from your network.
<p>
<dl compact><dt><b>Parameters:</b></dt><dd>
<table border="0" cellspacing="2" cellpadding="0">
<tr><td valign="top"></td><td valign="top"><em>ex</em>&nbsp;</td><td>Expected output values </td></tr>
</table>
</dl>
</div>
</div><p>
<a class="anchor" name="b0bd1daadb06980dff1f50d33a7c098e"></a><!-- doxytag: member="neuralpp::NeuralNet::update" ref="b0bd1daadb06980dff1f50d33a7c098e" args="()" -->
@ -540,17 +574,18 @@ It updates through back-propagation the weights of the synapsis and computes aga
<p>
It propagates values through the network.
<p>
Use this when you want to give an already trained network some new values the get to the output
Use this when you want to give an already trained network some new values the get to the output <dl compact><dt><b>Examples: </b></dt><dd>
<a class="el" href="examples_2adderFromScratch_8cpp-example.html#a3">examples/adderFromScratch.cpp</a>, and <a class="el" href="examples_2doAdd_8cpp-example.html#a4">examples/doAdd.cpp</a>.</dl>
</div>
</div><p>
<a class="anchor" name="0de170e8ab561ad63d0739b4c4b74f68"></a><!-- doxytag: member="neuralpp::NeuralNet::setInput" ref="0de170e8ab561ad63d0739b4c4b74f68" args="(vector&lt; double &gt; &amp;v)" -->
<a class="anchor" name="405b32d2928344314ecf0469070b0f17"></a><!-- doxytag: member="neuralpp::NeuralNet::setInput" ref="405b32d2928344314ecf0469070b0f17" args="(std::vector&lt; double &gt; v)" -->
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<td class="memname">void neuralpp::NeuralNet::setInput </td>
<td>(</td>
<td class="paramtype">vector&lt; double &gt; &amp;&nbsp;</td>
<td class="paramtype">std::vector&lt; double &gt;&nbsp;</td>
<td class="paramname"> <em>v</em> </td>
<td>&nbsp;)&nbsp;</td>
<td></td>
@ -567,7 +602,8 @@ It sets the input for the network.
<tr><td valign="top"></td><td valign="top"><em>v</em>&nbsp;</td><td>Vector of doubles, containing the values to give to your network </td></tr>
</table>
</dl>
<dl compact><dt><b>Examples: </b></dt><dd>
<a class="el" href="examples_2adderFromScratch_8cpp-example.html#a2">examples/adderFromScratch.cpp</a>, and <a class="el" href="examples_2doAdd_8cpp-example.html#a3">examples/doAdd.cpp</a>.</dl>
</div>
</div><p>
<a class="anchor" name="46f23f462318a4ffc037a4e806364c3f"></a><!-- doxytag: member="neuralpp::NeuralNet::link" ref="46f23f462318a4ffc037a4e806364c3f" args="()" -->
@ -601,7 +637,7 @@ Don't use unless you exactly know what you're doing, it is already called by the
<td class="paramtype">const char *&nbsp;</td>
<td class="paramname"> <em>fname</em> </td>
<td>&nbsp;)&nbsp;</td>
<td> throw (NetworkFileWriteException)</td>
<td> throw (<a class="el" href="classneuralpp_1_1NetworkFileWriteException.html">NetworkFileWriteException</a>)</td>
</tr>
</table>
</div>
@ -617,20 +653,21 @@ Save a trained neural network to a binary file.
</dl>
<dl compact><dt><b>Exceptions:</b></dt><dd>
<table border="0" cellspacing="2" cellpadding="0">
<tr><td valign="top"></td><td valign="top"><em>NetworkFileWriteException</em>&nbsp;</td><td>When you get an error writing the network's information to a file </td></tr>
<tr><td valign="top"></td><td valign="top"><em><a class="el" href="classneuralpp_1_1NetworkFileWriteException.html" title="Exception thrown when trying to write the network&#39;s information to a file that...">NetworkFileWriteException</a></em>&nbsp;</td><td>When you get an error writing the network's information to a file </td></tr>
</table>
</dl>
<dl compact><dt><b>Examples: </b></dt><dd>
<a class="el" href="examples_2learnAdd_8cpp-example.html#a2">examples/learnAdd.cpp</a>.</dl>
</div>
</div><p>
<a class="anchor" name="ead4bdef0602a5cadbe3beb685e01f5f"></a><!-- doxytag: member="neuralpp::NeuralNet::train" ref="ead4bdef0602a5cadbe3beb685e01f5f" args="(string xml, source src)" -->
<a class="anchor" name="1c9e17437d41a7048611e21a3cc1c7dd"></a><!-- doxytag: member="neuralpp::NeuralNet::train" ref="1c9e17437d41a7048611e21a3cc1c7dd" args="(std::string xml, source src)" -->
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<td class="memname">void neuralpp::NeuralNet::train </td>
<td>(</td>
<td class="paramtype">string&nbsp;</td>
<td class="paramtype">std::string&nbsp;</td>
<td class="paramname"> <em>xml</em>, </td>
</tr>
<tr>
@ -642,7 +679,7 @@ Save a trained neural network to a binary file.
<tr>
<td></td>
<td>)</td>
<td></td><td></td><td> throw (InvalidXMLException)</td>
<td></td><td></td><td> throw (<a class="el" href="classneuralpp_1_1InvalidXMLException.html">InvalidXMLException</a>)</td>
</tr>
</table>
</div>
@ -659,20 +696,21 @@ A sample XML file is available in examples/adder.xml <dl compact><dt><b>Paramete
</dl>
<dl compact><dt><b>Exceptions:</b></dt><dd>
<table border="0" cellspacing="2" cellpadding="0">
<tr><td valign="top"></td><td valign="top"><em>InvalidXMLException</em>&nbsp;</td><td></td></tr>
<tr><td valign="top"></td><td valign="top"><em><a class="el" href="classneuralpp_1_1InvalidXMLException.html" title="Exception thrown when trying parsing an invalid XML.">InvalidXMLException</a></em>&nbsp;</td><td></td></tr>
</table>
</dl>
<dl compact><dt><b>Examples: </b></dt><dd>
<a class="el" href="examples_2adderFromScratch_8cpp-example.html#a1">examples/adderFromScratch.cpp</a>, and <a class="el" href="examples_2learnAdd_8cpp-example.html#a1">examples/learnAdd.cpp</a>.</dl>
</div>
</div><p>
<a class="anchor" name="45c7645d4affe65752d37cd230afba24"></a><!-- doxytag: member="neuralpp::NeuralNet::initXML" ref="45c7645d4affe65752d37cd230afba24" args="(string &amp;xml)" -->
<a class="anchor" name="96da6712a72051cf34ad961761ef6e08"></a><!-- doxytag: member="neuralpp::NeuralNet::initXML" ref="96da6712a72051cf34ad961761ef6e08" args="(std::string &amp;xml)" -->
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<td class="memname">static void neuralpp::NeuralNet::initXML </td>
<td>(</td>
<td class="paramtype">string &amp;&nbsp;</td>
<td class="paramtype">std::string &amp;&nbsp;</td>
<td class="paramname"> <em>xml</em> </td>
<td>&nbsp;)&nbsp;</td>
<td><code> [static]</code></td>
@ -692,12 +730,12 @@ Initialize the training XML for the neural network.
</div>
</div><p>
<a class="anchor" name="e07af23ceb8666518da0c035bf1e0376"></a><!-- doxytag: member="neuralpp::NeuralNet::split" ref="e07af23ceb8666518da0c035bf1e0376" args="(char delim, string str)" -->
<a class="anchor" name="83c6555520856d5867752904349ab6ca"></a><!-- doxytag: member="neuralpp::NeuralNet::split" ref="83c6555520856d5867752904349ab6ca" args="(char delim, std::string str)" -->
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<td class="memname">static vector&lt;double&gt; neuralpp::NeuralNet::split </td>
<td class="memname">static std::vector&lt;double&gt; neuralpp::NeuralNet::split </td>
<td>(</td>
<td class="paramtype">char&nbsp;</td>
<td class="paramname"> <em>delim</em>, </td>
@ -705,7 +743,7 @@ Initialize the training XML for the neural network.
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">string&nbsp;</td>
<td class="paramtype">std::string&nbsp;</td>
<td class="paramname"> <em>str</em></td><td>&nbsp;</td>
</tr>
<tr>
@ -730,20 +768,20 @@ Splits a string into a vector of doubles, given a delimitator.
</div>
</div><p>
<a class="anchor" name="4be31ecb0b543a192997bd83c6995ccb"></a><!-- doxytag: member="neuralpp::NeuralNet::XMLFromSet" ref="4be31ecb0b543a192997bd83c6995ccb" args="(int id, string set)" -->
<a class="anchor" name="0a2733037af912b3e6a10146e7b7172f"></a><!-- doxytag: member="neuralpp::NeuralNet::XMLFromSet" ref="0a2733037af912b3e6a10146e7b7172f" args="(int &amp;id, std::string set)" -->
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<td class="memname">static string neuralpp::NeuralNet::XMLFromSet </td>
<td class="memname">static std::string neuralpp::NeuralNet::XMLFromSet </td>
<td>(</td>
<td class="paramtype">int&nbsp;</td>
<td class="paramtype">int &amp;&nbsp;</td>
<td class="paramname"> <em>id</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">string&nbsp;</td>
<td class="paramtype">std::string&nbsp;</td>
<td class="paramname"> <em>set</em></td><td>&nbsp;</td>
</tr>
<tr>
@ -768,14 +806,14 @@ Get a training set from a string and copies it to an XML For example, these stri
</div>
</div><p>
<a class="anchor" name="28b9966c5f197b8e86d57dd104aa32a6"></a><!-- doxytag: member="neuralpp::NeuralNet::closeXML" ref="28b9966c5f197b8e86d57dd104aa32a6" args="(string &amp;xml)" -->
<a class="anchor" name="e17732ed578bc4bd6032bfae58a5cf51"></a><!-- doxytag: member="neuralpp::NeuralNet::closeXML" ref="e17732ed578bc4bd6032bfae58a5cf51" args="(std::string &amp;xml)" -->
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<td class="memname">static void neuralpp::NeuralNet::closeXML </td>
<td>(</td>
<td class="paramtype">string &amp;&nbsp;</td>
<td class="paramtype">std::string &amp;&nbsp;</td>
<td class="paramname"> <em>xml</em> </td>
<td>&nbsp;)&nbsp;</td>
<td><code> [static]</code></td>
@ -841,12 +879,27 @@ Closes an open XML document generated by "initXML" and "XMLFromSet".
</div>
</div><p>
<a class="anchor" name="261f5f68fcc5be54250cfa03945266dd"></a><!-- doxytag: member="neuralpp::NeuralNet::ex" ref="261f5f68fcc5be54250cfa03945266dd" args="" -->
<a class="anchor" name="327dbfdd72b0a74293f8f29630525aa3"></a><!-- doxytag: member="neuralpp::NeuralNet::threshold" ref="327dbfdd72b0a74293f8f29630525aa3" args="" -->
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<td class="memname">double <a class="el" href="classneuralpp_1_1NeuralNet.html#261f5f68fcc5be54250cfa03945266dd">neuralpp::NeuralNet::ex</a><code> [private]</code> </td>
<td class="memname">double <a class="el" href="classneuralpp_1_1NeuralNet.html#327dbfdd72b0a74293f8f29630525aa3">neuralpp::NeuralNet::threshold</a><code> [private]</code> </td>
</tr>
</table>
</div>
<div class="memdoc">
<p>
</div>
</div><p>
<a class="anchor" name="a9e4ff43427f56663739c4c7450de8ee"></a><!-- doxytag: member="neuralpp::NeuralNet::expect" ref="a9e4ff43427f56663739c4c7450de8ee" args="" -->
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<td class="memname">std::vector&lt;double&gt; <a class="el" href="classneuralpp_1_1NeuralNet.html#a9e4ff43427f56663739c4c7450de8ee">neuralpp::NeuralNet::expect</a><code> [private]</code> </td>
</tr>
</table>
</div>
@ -921,7 +974,7 @@ Private pointer to function, containing the function to be used as activation fu
<hr>The documentation for this class was generated from the following file:<ul>
<li><a class="el" href="neural_09_09_8hpp-source.html">neural++.hpp</a></ul>
</div>
<hr size="1"><address style="text-align: right;"><small>Generated on Sat Aug 15 02:56:02 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<a href="http://www.doxygen.org/index.html">
<img src="doxygen.png" alt="doxygen" align="middle" border="0"></a> 1.5.6 </small></address>
</body>

View file

@ -12,6 +12,7 @@
<li><a href="namespaces.html"><span>Namespaces</span></a></li>
<li class="current"><a href="annotated.html"><span>Classes</span></a></li>
<li><a href="files.html"><span>Files</span></a></li>
<li><a href="examples.html"><span>Examples</span></a></li>
</ul>
</div>
<div class="tabs">
@ -27,23 +28,24 @@
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1Neuron.html#eec680c47272b2465e8d8a998c359853">actv_val</a></td><td><a class="el" href="classneuralpp_1_1Neuron.html">neuralpp::Neuron</a></td><td><code> [private]</code></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1Neuron.html#55993867179f0ac7d1e0e2c460ceb611">getActv</a>()</td><td><a class="el" href="classneuralpp_1_1Neuron.html">neuralpp::Neuron</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1Neuron.html#57c022f82213f662e2a263fc134a3fc9">getProp</a>()</td><td><a class="el" href="classneuralpp_1_1Neuron.html">neuralpp::Neuron</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1Neuron.html#ead827210fa18c2baae03927b2c798ff">in</a></td><td><a class="el" href="classneuralpp_1_1Neuron.html">neuralpp::Neuron</a></td><td><code> [private]</code></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1Neuron.html#9863a08b73bc97c8b514aca6c580ff7b">Neuron</a>(double(*a)(double))</td><td><a class="el" href="classneuralpp_1_1Neuron.html">neuralpp::Neuron</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1Neuron.html#f1bf19ec93174f60b368ee4a91b03f46">Neuron</a>(vector&lt; Synapsis &gt; in, vector&lt; Synapsis &gt; out, double(*a)(double))</td><td><a class="el" href="classneuralpp_1_1Neuron.html">neuralpp::Neuron</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1Neuron.html#bd07357465bb7b29bb344400e9e08710">in</a></td><td><a class="el" href="classneuralpp_1_1Neuron.html">neuralpp::Neuron</a></td><td><code> [private]</code></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1Neuron.html#c9bd4f5f618fcf1adcebf1ab63ee0960">Neuron</a>(double(*a)(double), double th=0.0)</td><td><a class="el" href="classneuralpp_1_1Neuron.html">neuralpp::Neuron</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1Neuron.html#d15e96b0316d880953288cc6e2550bec">Neuron</a>(std::vector&lt; Synapsis &gt; in, std::vector&lt; Synapsis &gt; out, double(*a)(double), double th=0.0)</td><td><a class="el" href="classneuralpp_1_1Neuron.html">neuralpp::Neuron</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1Neuron.html#ad97f1a082d5f969eb4c69ab454ecfbb">nIn</a>()</td><td><a class="el" href="classneuralpp_1_1Neuron.html">neuralpp::Neuron</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1Neuron.html#fe458021e3b20d58dc608fb94ae2135b">nOut</a>()</td><td><a class="el" href="classneuralpp_1_1Neuron.html">neuralpp::Neuron</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1Neuron.html#82a4297f84d6403e52a8386d26117b4f">out</a></td><td><a class="el" href="classneuralpp_1_1Neuron.html">neuralpp::Neuron</a></td><td><code> [private]</code></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1Neuron.html#982aceef324b7764e778d5949720bc55">out</a></td><td><a class="el" href="classneuralpp_1_1Neuron.html">neuralpp::Neuron</a></td><td><code> [private]</code></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1Neuron.html#da75259de98b1a893c736666af6bfdc3">prop_val</a></td><td><a class="el" href="classneuralpp_1_1Neuron.html">neuralpp::Neuron</a></td><td><code> [private]</code></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1Neuron.html#8b0ca61cd0e047c8691ab39aae56dbda">propagate</a>()</td><td><a class="el" href="classneuralpp_1_1Neuron.html">neuralpp::Neuron</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1Neuron.html#583ada6e1dd3f2e113415b4d89196e62">push_in</a>(Synapsis &amp;s)</td><td><a class="el" href="classneuralpp_1_1Neuron.html">neuralpp::Neuron</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1Neuron.html#bca65db84f56f9d40694bfbcd25812cb">push_out</a>(Synapsis &amp;s)</td><td><a class="el" href="classneuralpp_1_1Neuron.html">neuralpp::Neuron</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1Neuron.html#928d9bf5aed600119c640779e4034f30">propagate</a>()</td><td><a class="el" href="classneuralpp_1_1Neuron.html">neuralpp::Neuron</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1Neuron.html#4d252151c35839975838539d846d70be">push_in</a>(Synapsis s)</td><td><a class="el" href="classneuralpp_1_1Neuron.html">neuralpp::Neuron</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1Neuron.html#2c0acb0e6d413c4e0fc9e7939da1a684">push_out</a>(Synapsis s)</td><td><a class="el" href="classneuralpp_1_1Neuron.html">neuralpp::Neuron</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1Neuron.html#ddf00ffef030b27ed11901aad08822bd">setActv</a>(double a)</td><td><a class="el" href="classneuralpp_1_1Neuron.html">neuralpp::Neuron</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1Neuron.html#aa6e58f073a76b3481fea9115a4e6ea6">setProp</a>(double p)</td><td><a class="el" href="classneuralpp_1_1Neuron.html">neuralpp::Neuron</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1Neuron.html#2e2ccb69277fc3d992a3a3f2360ed154">synClear</a>()</td><td><a class="el" href="classneuralpp_1_1Neuron.html">neuralpp::Neuron</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1Neuron.html#29f2d9dcc4ca34f224d4dc39bb2f180a">synIn</a>(size_t i)</td><td><a class="el" href="classneuralpp_1_1Neuron.html">neuralpp::Neuron</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1Neuron.html#655f1637e1b754461413ac7fc2ffeebe">synOut</a>(size_t i)</td><td><a class="el" href="classneuralpp_1_1Neuron.html">neuralpp::Neuron</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1Neuron.html#7b16632868821d73dedcb8edaf6dbbef">threshold</a></td><td><a class="el" href="classneuralpp_1_1Neuron.html">neuralpp::Neuron</a></td><td><code> [private]</code></td></tr>
</table></div>
<hr size="1"><address style="text-align: right;"><small>Generated on Sat Aug 15 02:56:02 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<a href="http://www.doxygen.org/index.html">
<img src="doxygen.png" alt="doxygen" align="middle" border="0"></a> 1.5.6 </small></address>
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View file

@ -12,6 +12,7 @@
<li><a href="namespaces.html"><span>Namespaces</span></a></li>
<li class="current"><a href="annotated.html"><span>Classes</span></a></li>
<li><a href="files.html"><span>Files</span></a></li>
<li><a href="examples.html"><span>Examples</span></a></li>
</ul>
</div>
<div class="tabs">
@ -34,24 +35,24 @@
<a href="classneuralpp_1_1Neuron-members.html">List of all members.</a><table border="0" cellpadding="0" cellspacing="0">
<tr><td></td></tr>
<tr><td colspan="2"><br><h2>Public Member Functions</h2></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1Neuron.html#9863a08b73bc97c8b514aca6c580ff7b">Neuron</a> (double(*a)(double))</td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1Neuron.html#c9bd4f5f618fcf1adcebf1ab63ee0960">Neuron</a> (double(*a)(double), double th=0.0)</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Constructor. <a href="#9863a08b73bc97c8b514aca6c580ff7b"></a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1Neuron.html#f1bf19ec93174f60b368ee4a91b03f46">Neuron</a> (vector&lt; <a class="el" href="classneuralpp_1_1Synapsis.html">Synapsis</a> &gt; <a class="el" href="classneuralpp_1_1Neuron.html#ead827210fa18c2baae03927b2c798ff">in</a>, vector&lt; <a class="el" href="classneuralpp_1_1Synapsis.html">Synapsis</a> &gt; <a class="el" href="classneuralpp_1_1Neuron.html#82a4297f84d6403e52a8386d26117b4f">out</a>, double(*a)(double))</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Constructor. <a href="#c9bd4f5f618fcf1adcebf1ab63ee0960"></a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1Neuron.html#d15e96b0316d880953288cc6e2550bec">Neuron</a> (std::vector&lt; <a class="el" href="classneuralpp_1_1Synapsis.html">Synapsis</a> &gt; <a class="el" href="classneuralpp_1_1Neuron.html#bd07357465bb7b29bb344400e9e08710">in</a>, std::vector&lt; <a class="el" href="classneuralpp_1_1Synapsis.html">Synapsis</a> &gt; <a class="el" href="classneuralpp_1_1Neuron.html#982aceef324b7764e778d5949720bc55">out</a>, double(*a)(double), double th=0.0)</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Alternative constructor, that gets also the synapsis linked to the neuron. <a href="#f1bf19ec93174f60b368ee4a91b03f46"></a><br></td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Alternative constructor, that gets also the synapsis linked to the neuron. <a href="#d15e96b0316d880953288cc6e2550bec"></a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="el" href="classneuralpp_1_1Synapsis.html">Synapsis</a> &amp;&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1Neuron.html#29f2d9dcc4ca34f224d4dc39bb2f180a">synIn</a> (size_t i)</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Get the i-th synapsis connected on the input of the neuron. <a href="#29f2d9dcc4ca34f224d4dc39bb2f180a"></a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="el" href="classneuralpp_1_1Synapsis.html">Synapsis</a> &amp;&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1Neuron.html#655f1637e1b754461413ac7fc2ffeebe">synOut</a> (size_t i)</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Get the i-th synapsis connected on the output of the neuron. <a href="#655f1637e1b754461413ac7fc2ffeebe"></a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">void&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1Neuron.html#583ada6e1dd3f2e113415b4d89196e62">push_in</a> (<a class="el" href="classneuralpp_1_1Synapsis.html">Synapsis</a> &amp;s)</td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">void&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1Neuron.html#4d252151c35839975838539d846d70be">push_in</a> (<a class="el" href="classneuralpp_1_1Synapsis.html">Synapsis</a> s)</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">It pushes a new input synapsis. <a href="#583ada6e1dd3f2e113415b4d89196e62"></a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">void&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1Neuron.html#bca65db84f56f9d40694bfbcd25812cb">push_out</a> (<a class="el" href="classneuralpp_1_1Synapsis.html">Synapsis</a> &amp;s)</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">It pushes a new input synapsis. <a href="#4d252151c35839975838539d846d70be"></a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">void&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1Neuron.html#2c0acb0e6d413c4e0fc9e7939da1a684">push_out</a> (<a class="el" href="classneuralpp_1_1Synapsis.html">Synapsis</a> s)</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">It pushes a new output synapsis. <a href="#bca65db84f56f9d40694bfbcd25812cb"></a><br></td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">It pushes a new output synapsis. <a href="#2c0acb0e6d413c4e0fc9e7939da1a684"></a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">void&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1Neuron.html#ddf00ffef030b27ed11901aad08822bd">setActv</a> (double a)</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Change the activation value of the neuron. <a href="#ddf00ffef030b27ed11901aad08822bd"></a><br></td></tr>
@ -64,9 +65,9 @@
<tr><td class="memItemLeft" nowrap align="right" valign="top">double&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1Neuron.html#57c022f82213f662e2a263fc134a3fc9">getProp</a> ()</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Get the propagation value of the neuron. <a href="#57c022f82213f662e2a263fc134a3fc9"></a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">double&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1Neuron.html#8b0ca61cd0e047c8691ab39aae56dbda">propagate</a> ()</td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">void&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1Neuron.html#928d9bf5aed600119c640779e4034f30">propagate</a> ()</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">It propagates its activation value to the connected neurons. <a href="#8b0ca61cd0e047c8691ab39aae56dbda"></a><br></td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Compute the propagation value of the neuron and set it. <a href="#928d9bf5aed600119c640779e4034f30"></a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">size_t&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1Neuron.html#ad97f1a082d5f969eb4c69ab454ecfbb">nIn</a> ()</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Get the number of input synapsis for the neuron. <a href="#ad97f1a082d5f969eb4c69ab454ecfbb"></a><br></td></tr>
@ -81,9 +82,11 @@
<tr><td class="memItemLeft" nowrap align="right" valign="top">double&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1Neuron.html#da75259de98b1a893c736666af6bfdc3">prop_val</a></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">vector&lt; <a class="el" href="classneuralpp_1_1Synapsis.html">Synapsis</a> &gt;&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1Neuron.html#ead827210fa18c2baae03927b2c798ff">in</a></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">double&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1Neuron.html#7b16632868821d73dedcb8edaf6dbbef">threshold</a></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">vector&lt; <a class="el" href="classneuralpp_1_1Synapsis.html">Synapsis</a> &gt;&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1Neuron.html#82a4297f84d6403e52a8386d26117b4f">out</a></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">std::vector&lt; <a class="el" href="classneuralpp_1_1Synapsis.html">Synapsis</a> &gt;&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1Neuron.html#bd07357465bb7b29bb344400e9e08710">in</a></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">std::vector&lt; <a class="el" href="classneuralpp_1_1Synapsis.html">Synapsis</a> &gt;&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1Neuron.html#982aceef324b7764e778d5949720bc55">out</a></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">double(*&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1Neuron.html#198ddd0d11a26d0052d52b787d6a0df0">actv_f</a> )(double)</td></tr>
@ -92,7 +95,7 @@
Class for managing neurons.
<p>
Don't use this class directly unless you know what you're doing, use <a class="el" href="classneuralpp_1_1NeuralNet.html" title="Main project&#39;s class.">NeuralNet</a> instead <hr><h2>Constructor &amp; Destructor Documentation</h2>
<a class="anchor" name="9863a08b73bc97c8b514aca6c580ff7b"></a><!-- doxytag: member="neuralpp::Neuron::Neuron" ref="9863a08b73bc97c8b514aca6c580ff7b" args="(double(*a)(double))" -->
<a class="anchor" name="c9bd4f5f618fcf1adcebf1ab63ee0960"></a><!-- doxytag: member="neuralpp::Neuron::Neuron" ref="c9bd4f5f618fcf1adcebf1ab63ee0960" args="(double(*a)(double), double th=0.0)" -->
<div class="memitem">
<div class="memproto">
<table class="memname">
@ -100,9 +103,18 @@ Don't use this class directly unless you know what you're doing, use <a class="e
<td class="memname">neuralpp::Neuron::Neuron </td>
<td>(</td>
<td class="paramtype">double(*)(double)&nbsp;</td>
<td class="paramname"> <em>a</em> </td>
<td>&nbsp;)&nbsp;</td>
<td class="paramname"> <em>a</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">double&nbsp;</td>
<td class="paramname"> <em>th</em> = <code>0.0</code></td><td>&nbsp;</td>
</tr>
<tr>
<td></td>
<td>)</td>
<td></td><td></td><td></td>
</tr>
</table>
</div>
@ -114,32 +126,39 @@ Constructor.
<dl compact><dt><b>Parameters:</b></dt><dd>
<table border="0" cellspacing="2" cellpadding="0">
<tr><td valign="top"></td><td valign="top"><em>a</em>&nbsp;</td><td>Activation function </td></tr>
<tr><td valign="top"></td><td valign="top"><em>th</em>&nbsp;</td><td>Threshold, value in [0,1] that establishes how much a neuron must be 'sensitive' on variations of the input values </td></tr>
</table>
</dl>
</div>
</div><p>
<a class="anchor" name="f1bf19ec93174f60b368ee4a91b03f46"></a><!-- doxytag: member="neuralpp::Neuron::Neuron" ref="f1bf19ec93174f60b368ee4a91b03f46" args="(vector&lt; Synapsis &gt; in, vector&lt; Synapsis &gt; out, double(*a)(double))" -->
<a class="anchor" name="d15e96b0316d880953288cc6e2550bec"></a><!-- doxytag: member="neuralpp::Neuron::Neuron" ref="d15e96b0316d880953288cc6e2550bec" args="(std::vector&lt; Synapsis &gt; in, std::vector&lt; Synapsis &gt; out, double(*a)(double), double th=0.0)" -->
<div class="memitem">
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<tr>
<td class="memname">neuralpp::Neuron::Neuron </td>
<td>(</td>
<td class="paramtype">vector&lt; <a class="el" href="classneuralpp_1_1Synapsis.html">Synapsis</a> &gt;&nbsp;</td>
<td class="paramtype">std::vector&lt; <a class="el" href="classneuralpp_1_1Synapsis.html">Synapsis</a> &gt;&nbsp;</td>
<td class="paramname"> <em>in</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">vector&lt; <a class="el" href="classneuralpp_1_1Synapsis.html">Synapsis</a> &gt;&nbsp;</td>
<td class="paramtype">std::vector&lt; <a class="el" href="classneuralpp_1_1Synapsis.html">Synapsis</a> &gt;&nbsp;</td>
<td class="paramname"> <em>out</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">double(*)(double)&nbsp;</td>
<td class="paramname"> <em>a</em></td><td>&nbsp;</td>
<td class="paramname"> <em>a</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">double&nbsp;</td>
<td class="paramname"> <em>th</em> = <code>0.0</code></td><td>&nbsp;</td>
</tr>
<tr>
<td></td>
@ -158,6 +177,7 @@ Alternative constructor, that gets also the synapsis linked to the neuron.
<tr><td valign="top"></td><td valign="top"><em>in</em>&nbsp;</td><td>Input synapses </td></tr>
<tr><td valign="top"></td><td valign="top"><em>out</em>&nbsp;</td><td>Output synapses </td></tr>
<tr><td valign="top"></td><td valign="top"><em>a</em>&nbsp;</td><td>Activation function </td></tr>
<tr><td valign="top"></td><td valign="top"><em>th</em>&nbsp;</td><td>Threshold, value in [0,1] that establishes how much a neuron must be 'sensitive' on variations of the input values </td></tr>
</table>
</dl>
@ -220,14 +240,14 @@ Get the i-th synapsis connected on the output of the neuron.
</div>
</div><p>
<a class="anchor" name="583ada6e1dd3f2e113415b4d89196e62"></a><!-- doxytag: member="neuralpp::Neuron::push_in" ref="583ada6e1dd3f2e113415b4d89196e62" args="(Synapsis &amp;s)" -->
<a class="anchor" name="4d252151c35839975838539d846d70be"></a><!-- doxytag: member="neuralpp::Neuron::push_in" ref="4d252151c35839975838539d846d70be" args="(Synapsis s)" -->
<div class="memitem">
<div class="memproto">
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<td class="memname">void neuralpp::Neuron::push_in </td>
<td>(</td>
<td class="paramtype"><a class="el" href="classneuralpp_1_1Synapsis.html">Synapsis</a> &amp;&nbsp;</td>
<td class="paramtype"><a class="el" href="classneuralpp_1_1Synapsis.html">Synapsis</a>&nbsp;</td>
<td class="paramname"> <em>s</em> </td>
<td>&nbsp;)&nbsp;</td>
<td></td>
@ -247,14 +267,14 @@ It pushes a new input synapsis.
</div>
</div><p>
<a class="anchor" name="bca65db84f56f9d40694bfbcd25812cb"></a><!-- doxytag: member="neuralpp::Neuron::push_out" ref="bca65db84f56f9d40694bfbcd25812cb" args="(Synapsis &amp;s)" -->
<a class="anchor" name="2c0acb0e6d413c4e0fc9e7939da1a684"></a><!-- doxytag: member="neuralpp::Neuron::push_out" ref="2c0acb0e6d413c4e0fc9e7939da1a684" args="(Synapsis s)" -->
<div class="memitem">
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<td class="memname">void neuralpp::Neuron::push_out </td>
<td>(</td>
<td class="paramtype"><a class="el" href="classneuralpp_1_1Synapsis.html">Synapsis</a> &amp;&nbsp;</td>
<td class="paramtype"><a class="el" href="classneuralpp_1_1Synapsis.html">Synapsis</a>&nbsp;</td>
<td class="paramname"> <em>s</em> </td>
<td>&nbsp;)&nbsp;</td>
<td></td>
@ -372,12 +392,12 @@ Get the propagation value of the neuron.
</div>
</div><p>
<a class="anchor" name="8b0ca61cd0e047c8691ab39aae56dbda"></a><!-- doxytag: member="neuralpp::Neuron::propagate" ref="8b0ca61cd0e047c8691ab39aae56dbda" args="()" -->
<a class="anchor" name="928d9bf5aed600119c640779e4034f30"></a><!-- doxytag: member="neuralpp::Neuron::propagate" ref="928d9bf5aed600119c640779e4034f30" args="()" -->
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<td class="memname">double neuralpp::Neuron::propagate </td>
<td class="memname">void neuralpp::Neuron::propagate </td>
<td>(</td>
<td class="paramname"> </td>
<td>&nbsp;)&nbsp;</td>
@ -388,7 +408,7 @@ Get the propagation value of the neuron.
<div class="memdoc">
<p>
It propagates its activation value to the connected neurons.
Compute the propagation value of the neuron and set it.
<p>
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@ -489,12 +509,12 @@ Remove input and output synapsis from a neuron.
</div>
</div><p>
<a class="anchor" name="ead827210fa18c2baae03927b2c798ff"></a><!-- doxytag: member="neuralpp::Neuron::in" ref="ead827210fa18c2baae03927b2c798ff" args="" -->
<a class="anchor" name="7b16632868821d73dedcb8edaf6dbbef"></a><!-- doxytag: member="neuralpp::Neuron::threshold" ref="7b16632868821d73dedcb8edaf6dbbef" args="" -->
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<td class="memname">vector&lt; <a class="el" href="classneuralpp_1_1Synapsis.html">Synapsis</a> &gt; <a class="el" href="classneuralpp_1_1Neuron.html#ead827210fa18c2baae03927b2c798ff">neuralpp::Neuron::in</a><code> [private]</code> </td>
<td class="memname">double <a class="el" href="classneuralpp_1_1Neuron.html#7b16632868821d73dedcb8edaf6dbbef">neuralpp::Neuron::threshold</a><code> [private]</code> </td>
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@ -504,12 +524,27 @@ Remove input and output synapsis from a neuron.
</div>
</div><p>
<a class="anchor" name="82a4297f84d6403e52a8386d26117b4f"></a><!-- doxytag: member="neuralpp::Neuron::out" ref="82a4297f84d6403e52a8386d26117b4f" args="" -->
<a class="anchor" name="bd07357465bb7b29bb344400e9e08710"></a><!-- doxytag: member="neuralpp::Neuron::in" ref="bd07357465bb7b29bb344400e9e08710" args="" -->
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<td class="memname">vector&lt; <a class="el" href="classneuralpp_1_1Synapsis.html">Synapsis</a> &gt; <a class="el" href="classneuralpp_1_1Neuron.html#82a4297f84d6403e52a8386d26117b4f">neuralpp::Neuron::out</a><code> [private]</code> </td>
<td class="memname">std::vector&lt; <a class="el" href="classneuralpp_1_1Synapsis.html">Synapsis</a> &gt; <a class="el" href="classneuralpp_1_1Neuron.html#bd07357465bb7b29bb344400e9e08710">neuralpp::Neuron::in</a><code> [private]</code> </td>
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</table>
</div>
<div class="memdoc">
<p>
</div>
</div><p>
<a class="anchor" name="982aceef324b7764e778d5949720bc55"></a><!-- doxytag: member="neuralpp::Neuron::out" ref="982aceef324b7764e778d5949720bc55" args="" -->
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<td class="memname">std::vector&lt; <a class="el" href="classneuralpp_1_1Synapsis.html">Synapsis</a> &gt; <a class="el" href="classneuralpp_1_1Neuron.html#982aceef324b7764e778d5949720bc55">neuralpp::Neuron::out</a><code> [private]</code> </td>
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@ -537,7 +572,7 @@ Remove input and output synapsis from a neuron.
<hr>The documentation for this class was generated from the following file:<ul>
<li><a class="el" href="neural_09_09_8hpp-source.html">neural++.hpp</a></ul>
</div>
<hr size="1"><address style="text-align: right;"><small>Generated on Sat Aug 15 02:56:02 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<a href="http://www.doxygen.org/index.html">
<img src="doxygen.png" alt="doxygen" align="middle" border="0"></a> 1.5.6 </small></address>
</body>

View file

@ -12,6 +12,7 @@
<li><a href="namespaces.html"><span>Namespaces</span></a></li>
<li class="current"><a href="annotated.html"><span>Classes</span></a></li>
<li><a href="files.html"><span>Files</span></a></li>
<li><a href="examples.html"><span>Examples</span></a></li>
</ul>
</div>
<div class="tabs">
@ -25,13 +26,13 @@
<h1>neuralpp::Synapsis Member List</h1>This is the complete list of members for <a class="el" href="classneuralpp_1_1Synapsis.html">neuralpp::Synapsis</a>, including all inherited members.<p><table>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1Synapsis.html#2539b9eef2ff0f3522aea8d89e394f02">actv_f</a></td><td><a class="el" href="classneuralpp_1_1Synapsis.html">neuralpp::Synapsis</a></td><td><code> [private]</code></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1Synapsis.html#617fdc4305f8f1850eac267a7ee22660">delta</a></td><td><a class="el" href="classneuralpp_1_1Synapsis.html">neuralpp::Synapsis</a></td><td><code> [private]</code></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1Synapsis.html#18f15b920609be8b818d43a0227aada5">getDelta</a>()</td><td><a class="el" href="classneuralpp_1_1Synapsis.html">neuralpp::Synapsis</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1Synapsis.html#5ba8a93a5741f4855390eb8a46e99435">getIn</a>()</td><td><a class="el" href="classneuralpp_1_1Synapsis.html">neuralpp::Synapsis</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1Synapsis.html#61c9a04e03291a01f44520cef143cbdd">getOut</a>()</td><td><a class="el" href="classneuralpp_1_1Synapsis.html">neuralpp::Synapsis</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1Synapsis.html#2fe3e9ec97542f1476d8b9306aa09756">getPrevDelta</a>()</td><td><a class="el" href="classneuralpp_1_1Synapsis.html">neuralpp::Synapsis</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1Synapsis.html#aa79c16ec6b59949e5d2f75a3f10d530">getWeight</a>()</td><td><a class="el" href="classneuralpp_1_1Synapsis.html">neuralpp::Synapsis</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1Synapsis.html#00c8e9c0804662f2b3247d6dddb4ca6c">getDelta</a>() const </td><td><a class="el" href="classneuralpp_1_1Synapsis.html">neuralpp::Synapsis</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1Synapsis.html#298fd3c7483ad572899fecec01ac8fdf">getIn</a>() const </td><td><a class="el" href="classneuralpp_1_1Synapsis.html">neuralpp::Synapsis</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1Synapsis.html#b46d876761a73a24db87f5a144a0e899">getOut</a>() const </td><td><a class="el" href="classneuralpp_1_1Synapsis.html">neuralpp::Synapsis</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1Synapsis.html#0148b9c8db870c928711168702ae51c5">getPrevDelta</a>() const </td><td><a class="el" href="classneuralpp_1_1Synapsis.html">neuralpp::Synapsis</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1Synapsis.html#bcbf7228632ff4d6bbb67703323d2db0">getWeight</a>() const </td><td><a class="el" href="classneuralpp_1_1Synapsis.html">neuralpp::Synapsis</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1Synapsis.html#83d41c158054b08bd05051736e89a0ad">in</a></td><td><a class="el" href="classneuralpp_1_1Synapsis.html">neuralpp::Synapsis</a></td><td><code> [private]</code></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1Synapsis.html#ecdb17182de791f7fdd417232e184350">momentum</a>(int N, int x)</td><td><a class="el" href="classneuralpp_1_1Synapsis.html">neuralpp::Synapsis</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1Synapsis.html#cff10a022d4c021688e4df944c05d8bd">momentum</a>(int N, int x) const </td><td><a class="el" href="classneuralpp_1_1Synapsis.html">neuralpp::Synapsis</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1Synapsis.html#fb219e05038fa0da20db1082ab0500be">out</a></td><td><a class="el" href="classneuralpp_1_1Synapsis.html">neuralpp::Synapsis</a></td><td><code> [private]</code></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1Synapsis.html#65471cd6c9ef87609dfa4b0e5fafa708">prev_delta</a></td><td><a class="el" href="classneuralpp_1_1Synapsis.html">neuralpp::Synapsis</a></td><td><code> [private]</code></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1Synapsis.html#429ad5b25930faf436a9d725582802e1">setDelta</a>(double d)</td><td><a class="el" href="classneuralpp_1_1Synapsis.html">neuralpp::Synapsis</a></td><td></td></tr>
@ -41,7 +42,7 @@
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1Synapsis.html#af6b80ab3203bccd2ee4a36f06537517">Synapsis</a>(Neuron *i, Neuron *o, double w, double(*a)(double))</td><td><a class="el" href="classneuralpp_1_1Synapsis.html">neuralpp::Synapsis</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1Synapsis.html#0bc523a8135ebbb5c0da932939d30ed7">weight</a></td><td><a class="el" href="classneuralpp_1_1Synapsis.html">neuralpp::Synapsis</a></td><td><code> [private]</code></td></tr>
</table></div>
<hr size="1"><address style="text-align: right;"><small>Generated on Sat Aug 15 02:56:02 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<a href="http://www.doxygen.org/index.html">
<img src="doxygen.png" alt="doxygen" align="middle" border="0"></a> 1.5.6 </small></address>
</body>

View file

@ -12,6 +12,7 @@
<li><a href="namespaces.html"><span>Namespaces</span></a></li>
<li class="current"><a href="annotated.html"><span>Classes</span></a></li>
<li><a href="files.html"><span>Files</span></a></li>
<li><a href="examples.html"><span>Examples</span></a></li>
</ul>
</div>
<div class="tabs">
@ -43,9 +44,9 @@
<tr><td class="memItemLeft" nowrap align="right" valign="top">&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1Synapsis.html#af6b80ab3203bccd2ee4a36f06537517">Synapsis</a> (<a class="el" href="classneuralpp_1_1Neuron.html">Neuron</a> *i, <a class="el" href="classneuralpp_1_1Neuron.html">Neuron</a> *o, double w, double(*a)(double))</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Constructor. <a href="#af6b80ab3203bccd2ee4a36f06537517"></a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="el" href="classneuralpp_1_1Neuron.html">Neuron</a> *&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1Synapsis.html#5ba8a93a5741f4855390eb8a46e99435">getIn</a> ()</td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="el" href="classneuralpp_1_1Neuron.html">Neuron</a> *&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1Synapsis.html#298fd3c7483ad572899fecec01ac8fdf">getIn</a> () const </td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="el" href="classneuralpp_1_1Neuron.html">Neuron</a> *&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1Synapsis.html#61c9a04e03291a01f44520cef143cbdd">getOut</a> ()</td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="el" href="classneuralpp_1_1Neuron.html">Neuron</a> *&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1Synapsis.html#b46d876761a73a24db87f5a144a0e899">getOut</a> () const </td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">void&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1Synapsis.html#acee77d0fdf9889464ab5ed27beae0ff">setWeight</a> (double w) throw (InvalidSynapticalWeightException)</td></tr>
@ -53,18 +54,18 @@
<tr><td class="memItemLeft" nowrap align="right" valign="top">void&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1Synapsis.html#429ad5b25930faf436a9d725582802e1">setDelta</a> (double d) throw (InvalidSynapticalWeightException)</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">It sets the delta (how much to change the weight after an update) of the synapsis. <a href="#429ad5b25930faf436a9d725582802e1"></a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">double&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1Synapsis.html#aa79c16ec6b59949e5d2f75a3f10d530">getWeight</a> ()</td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">double&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1Synapsis.html#bcbf7228632ff4d6bbb67703323d2db0">getWeight</a> () const </td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Return the weight of the synapsis. <a href="#aa79c16ec6b59949e5d2f75a3f10d530"></a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">double&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1Synapsis.html#18f15b920609be8b818d43a0227aada5">getDelta</a> ()</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Return the weight of the synapsis. <a href="#bcbf7228632ff4d6bbb67703323d2db0"></a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">double&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1Synapsis.html#00c8e9c0804662f2b3247d6dddb4ca6c">getDelta</a> () const </td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Return the delta of the synapsis. <a href="#18f15b920609be8b818d43a0227aada5"></a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">double&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1Synapsis.html#2fe3e9ec97542f1476d8b9306aa09756">getPrevDelta</a> ()</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Return the delta of the synapsis. <a href="#00c8e9c0804662f2b3247d6dddb4ca6c"></a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">double&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1Synapsis.html#0148b9c8db870c928711168702ae51c5">getPrevDelta</a> () const </td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Get the delta of the synapsis at the previous iteration. <a href="#2fe3e9ec97542f1476d8b9306aa09756"></a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">double&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1Synapsis.html#ecdb17182de791f7fdd417232e184350">momentum</a> (int N, int x)</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Get the delta of the synapsis at the previous iteration. <a href="#0148b9c8db870c928711168702ae51c5"></a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">double&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1Synapsis.html#cff10a022d4c021688e4df944c05d8bd">momentum</a> (int N, int x) const </td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Get the inertial momentum of a synapsis. <a href="#ecdb17182de791f7fdd417232e184350"></a><br></td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Get the inertial momentum of a synapsis. <a href="#cff10a022d4c021688e4df944c05d8bd"></a><br></td></tr>
<tr><td colspan="2"><br><h2>Private Attributes</h2></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">double&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1Synapsis.html#617fdc4305f8f1850eac267a7ee22660">delta</a></td></tr>
@ -230,7 +231,7 @@ Constructor.
</div>
</div><p>
<hr><h2>Member Function Documentation</h2>
<a class="anchor" name="5ba8a93a5741f4855390eb8a46e99435"></a><!-- doxytag: member="neuralpp::Synapsis::getIn" ref="5ba8a93a5741f4855390eb8a46e99435" args="()" -->
<a class="anchor" name="298fd3c7483ad572899fecec01ac8fdf"></a><!-- doxytag: member="neuralpp::Synapsis::getIn" ref="298fd3c7483ad572899fecec01ac8fdf" args="() const " -->
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@ -239,7 +240,7 @@ Constructor.
<td>(</td>
<td class="paramname"> </td>
<td>&nbsp;)&nbsp;</td>
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<td> const</td>
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@ -250,7 +251,7 @@ Constructor.
</div>
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<a class="anchor" name="61c9a04e03291a01f44520cef143cbdd"></a><!-- doxytag: member="neuralpp::Synapsis::getOut" ref="61c9a04e03291a01f44520cef143cbdd" args="()" -->
<a class="anchor" name="b46d876761a73a24db87f5a144a0e899"></a><!-- doxytag: member="neuralpp::Synapsis::getOut" ref="b46d876761a73a24db87f5a144a0e899" args="() const " -->
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@ -259,7 +260,7 @@ Constructor.
<td>(</td>
<td class="paramname"> </td>
<td>&nbsp;)&nbsp;</td>
<td></td>
<td> const</td>
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@ -280,7 +281,7 @@ Constructor.
<td class="paramtype">double&nbsp;</td>
<td class="paramname"> <em>w</em> </td>
<td>&nbsp;)&nbsp;</td>
<td> throw (InvalidSynapticalWeightException)</td>
<td> throw (<a class="el" href="classneuralpp_1_1InvalidSynapticalWeightException.html">InvalidSynapticalWeightException</a>)</td>
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@ -307,7 +308,7 @@ Set the weight of the synapsis.
<td class="paramtype">double&nbsp;</td>
<td class="paramname"> <em>d</em> </td>
<td>&nbsp;)&nbsp;</td>
<td> throw (InvalidSynapticalWeightException)</td>
<td> throw (<a class="el" href="classneuralpp_1_1InvalidSynapticalWeightException.html">InvalidSynapticalWeightException</a>)</td>
</tr>
</table>
</div>
@ -324,7 +325,7 @@ It sets the delta (how much to change the weight after an update) of the synapsi
</div>
</div><p>
<a class="anchor" name="aa79c16ec6b59949e5d2f75a3f10d530"></a><!-- doxytag: member="neuralpp::Synapsis::getWeight" ref="aa79c16ec6b59949e5d2f75a3f10d530" args="()" -->
<a class="anchor" name="bcbf7228632ff4d6bbb67703323d2db0"></a><!-- doxytag: member="neuralpp::Synapsis::getWeight" ref="bcbf7228632ff4d6bbb67703323d2db0" args="() const " -->
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@ -333,7 +334,7 @@ It sets the delta (how much to change the weight after an update) of the synapsi
<td>(</td>
<td class="paramname"> </td>
<td>&nbsp;)&nbsp;</td>
<td></td>
<td> const</td>
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@ -346,7 +347,7 @@ Return the weight of the synapsis.
</div>
</div><p>
<a class="anchor" name="18f15b920609be8b818d43a0227aada5"></a><!-- doxytag: member="neuralpp::Synapsis::getDelta" ref="18f15b920609be8b818d43a0227aada5" args="()" -->
<a class="anchor" name="00c8e9c0804662f2b3247d6dddb4ca6c"></a><!-- doxytag: member="neuralpp::Synapsis::getDelta" ref="00c8e9c0804662f2b3247d6dddb4ca6c" args="() const " -->
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@ -355,7 +356,7 @@ Return the weight of the synapsis.
<td>(</td>
<td class="paramname"> </td>
<td>&nbsp;)&nbsp;</td>
<td></td>
<td> const</td>
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@ -368,7 +369,7 @@ Return the delta of the synapsis.
</div>
</div><p>
<a class="anchor" name="2fe3e9ec97542f1476d8b9306aa09756"></a><!-- doxytag: member="neuralpp::Synapsis::getPrevDelta" ref="2fe3e9ec97542f1476d8b9306aa09756" args="()" -->
<a class="anchor" name="0148b9c8db870c928711168702ae51c5"></a><!-- doxytag: member="neuralpp::Synapsis::getPrevDelta" ref="0148b9c8db870c928711168702ae51c5" args="() const " -->
<div class="memitem">
<div class="memproto">
<table class="memname">
@ -377,7 +378,7 @@ Return the delta of the synapsis.
<td>(</td>
<td class="paramname"> </td>
<td>&nbsp;)&nbsp;</td>
<td></td>
<td> const</td>
</tr>
</table>
</div>
@ -390,7 +391,7 @@ Get the delta of the synapsis at the previous iteration.
</div>
</div><p>
<a class="anchor" name="ecdb17182de791f7fdd417232e184350"></a><!-- doxytag: member="neuralpp::Synapsis::momentum" ref="ecdb17182de791f7fdd417232e184350" args="(int N, int x)" -->
<a class="anchor" name="cff10a022d4c021688e4df944c05d8bd"></a><!-- doxytag: member="neuralpp::Synapsis::momentum" ref="cff10a022d4c021688e4df944c05d8bd" args="(int N, int x) const " -->
<div class="memitem">
<div class="memproto">
<table class="memname">
@ -409,7 +410,7 @@ Get the delta of the synapsis at the previous iteration.
<tr>
<td></td>
<td>)</td>
<td></td><td></td><td></td>
<td></td><td></td><td> const</td>
</tr>
</table>
</div>
@ -522,7 +523,7 @@ This value is inversely proportional to the number of steps done in the learning
<hr>The documentation for this class was generated from the following file:<ul>
<li><a class="el" href="neural_09_09_8hpp-source.html">neural++.hpp</a></ul>
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<title>Neural++: Examples</title>
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<h1>Examples</h1>Here is a list of all examples:<ul>
<li><a class="el" href="examples_2adderFromScratch_8cpp-example.html">examples/adderFromScratch.cpp</a>
<li><a class="el" href="examples_2doAdd_8cpp-example.html">examples/doAdd.cpp</a>
<li><a class="el" href="examples_2learnAdd_8cpp-example.html">examples/learnAdd.cpp</a>
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<title>Neural++: examples/adderFromScratch.cpp</title>
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<h1>examples/adderFromScratch.cpp</h1>Similar to learnAdd.cpp, but this time the training XML is generated as a string and not saved to a file, and parsed by the program itself to build the network. Then, the program asks two real numbers, and performs both the sum and the difference between them, putting the sum's output on the first output neuron and the difference's on the second output neuron. Anyway, using more than one neuron in the output layer is strongly discouraged, as the network usually won't set correctly the synaptical weights to give satisfying and accurate answers for all of the operations.<p>
<div class="fragment"><pre class="fragment">
<span class="preprocessor">#include &lt;iostream&gt;</span>
<span class="preprocessor">#include &lt;<a class="code" href="neural_09_09_8hpp.html">neural++.hpp</a>&gt;</span>
<span class="keyword">using namespace </span>std;
<span class="keyword">using namespace </span>neuralpp;
<span class="keywordtype">int</span> main() {
<a name="_a0"></a><a class="code" href="classneuralpp_1_1NeuralNet.html" title="Main project&amp;#39;s class.">NeuralNet</a> net(2, 2, 2, 0.005, 100);
<span class="keywordtype">string</span> xml;
<span class="keywordtype">double</span> tmp;
<span class="keywordtype">int</span> <span class="keywordtype">id</span> = 0;
<span class="comment">// XML initialization. Then, I say XML that 2+3=5, 3+3=6, 5+4=9</span>
<span class="comment">// Strings' format is "input1,input2,...,inputn;output1,output2,...,outputm</span>
NeuralNet::initXML(xml);
xml += NeuralNet::XMLFromSet(<span class="keywordtype">id</span>, <span class="stringliteral">"3,2;5,1"</span>);
xml += NeuralNet::XMLFromSet(<span class="keywordtype">id</span>, <span class="stringliteral">"4,2;6,2"</span>);
xml += NeuralNet::XMLFromSet(<span class="keywordtype">id</span>, <span class="stringliteral">"6,3;9,3"</span>);
NeuralNet::closeXML(xml);
cout &lt;&lt; xml &lt;&lt; endl;
net.<a name="a1"></a><a class="code" href="classneuralpp_1_1NeuralNet.html#1c9e17437d41a7048611e21a3cc1c7dd" title="Train a network using a training set loaded from an XML file.">train</a>(xml, NeuralNet::str);
vector&lt;double&gt; v;
cout &lt;&lt; <span class="stringliteral">"Network status: trained\n\n"</span>;
cout &lt;&lt; <span class="stringliteral">"First number to add: "</span>;
cin &gt;&gt; tmp;
v.push_back(tmp);
cout &lt;&lt; <span class="stringliteral">"Second number to add: "</span>;
cin &gt;&gt; tmp;
v.push_back(tmp);
net.<a name="a2"></a><a class="code" href="classneuralpp_1_1NeuralNet.html#405b32d2928344314ecf0469070b0f17" title="It sets the input for the network.">setInput</a>(v);
net.<a name="a3"></a><a class="code" href="classneuralpp_1_1NeuralNet.html#c129c180647362da963758bfd1ba6890" title="It propagates values through the network.">propagate</a>();
cout &lt;&lt; <span class="stringliteral">"Output: "</span> &lt;&lt; net.<a name="a4"></a><a class="code" href="classneuralpp_1_1NeuralNet.html#e6d2215ecc8b560db2f6797db642191c" title="It gets the output of the network in case the output layer contains more neurons...">getOutputs</a>()[0] &lt;&lt; <span class="stringliteral">"; "</span> &lt;&lt; net.<a class="code" href="classneuralpp_1_1NeuralNet.html#e6d2215ecc8b560db2f6797db642191c" title="It gets the output of the network in case the output layer contains more neurons...">getOutputs</a>()[1] &lt;&lt; endl;
<span class="keywordflow">return</span> 0;
}
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<title>Neural++: examples/doAdd.cpp</title>
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<h1>examples/doAdd.cpp</h1>Show how to use a network already trained and saved to a binary file. In this case, a network trained to simply perform sums between two real numbers, that should have already been created using learnAdd.<p>
<div class="fragment"><pre class="fragment">
<span class="preprocessor">#include &lt;iostream&gt;</span>
<span class="preprocessor">#include &lt;<a class="code" href="neural_09_09_8hpp.html">neural++.hpp</a>&gt;</span>
<span class="keyword">using namespace </span>std;
<span class="keyword">using namespace </span>neuralpp;
<span class="preprocessor">#define NETFILE "adder.net"</span>
<span class="preprocessor"></span>
<span class="keywordtype">int</span> main() {
<span class="keywordtype">double</span> a,b;
<a name="_a0"></a><a class="code" href="classneuralpp_1_1NeuralNet.html" title="Main project&amp;#39;s class.">NeuralNet</a> net;
<span class="comment">// Load the pre-trained network from "adder.net" file</span>
<span class="keywordflow">try</span> {
net = <a class="code" href="classneuralpp_1_1NeuralNet.html" title="Main project&amp;#39;s class.">NeuralNet</a>(NETFILE);
}
<span class="keywordflow">catch</span> (<a name="_a1"></a><a class="code" href="classneuralpp_1_1NetworkFileNotFoundException.html" title="Exception thrown when doing an attempt to load a network from an invalid file.">NetworkFileNotFoundException</a> e) {
cerr &lt;&lt; <span class="stringliteral">"Fatal error while opening "</span> &lt;&lt; NETFILE &lt;&lt; <span class="stringliteral">": "</span> &lt;&lt; e.<a name="a2"></a><a class="code" href="classneuralpp_1_1NetworkFileNotFoundException.html#24cde7729ab22d343f36e638cfc40702">what</a>();
<span class="keywordflow">return</span> 1;
}
cout &lt;&lt; <span class="stringliteral">"First number to add: "</span>;
cin &gt;&gt; a;
cout &lt;&lt; <span class="stringliteral">"Second number to add: "</span>;
cin &gt;&gt; b;
vector&lt;double&gt; v;
v.push_back(a);
v.push_back(b);
<span class="comment">// Set the numbers just read as input values, propagate those values, and get</span>
<span class="comment">// the output</span>
net.<a name="a3"></a><a class="code" href="classneuralpp_1_1NeuralNet.html#405b32d2928344314ecf0469070b0f17" title="It sets the input for the network.">setInput</a>(v);
net.<a name="a4"></a><a class="code" href="classneuralpp_1_1NeuralNet.html#c129c180647362da963758bfd1ba6890" title="It propagates values through the network.">propagate</a>();
cout &lt;&lt; <span class="stringliteral">"Neural net output: "</span> &lt;&lt; net.<a name="a5"></a><a class="code" href="classneuralpp_1_1NeuralNet.html#961dce8913264bf64c899dce4e25f810" title="It gets the output of the network (note: the layer output should contain an only...">getOutput</a>() &lt;&lt; endl;
<span class="keywordflow">return</span> 0;
}
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<title>Neural++: examples/learnAdd.cpp</title>
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<h1>examples/learnAdd.cpp</h1>Show how to train a network that performs sums between two real numbers. The training XML is built from scratch, then saved to a file, then the network is initialized using that XML file, trained, and the resulting trained network is saved to adder.net. Then, you should take a look at doAdd.cpp to see how to use that file to use the network.<p>
<div class="fragment"><pre class="fragment">
<span class="preprocessor">#include &lt;iostream&gt;</span>
<span class="preprocessor">#include &lt;fstream&gt;</span>
<span class="preprocessor">#include &lt;ctime&gt;</span>
<span class="preprocessor">#include &lt;<a class="code" href="neural_09_09_8hpp.html">neural++.hpp</a>&gt;</span>
<span class="keyword">using namespace </span>std;
<span class="keyword">using namespace </span>neuralpp;
<span class="keywordtype">int</span> main() {
<span class="keywordtype">int</span> <span class="keywordtype">id</span> = 0;
<span class="keywordtype">string</span> xml;
time_t t1, t2;
<span class="comment">// Create the neural network. The network is going to have</span>
<span class="comment">// =&gt; 2 neurons for the input layer</span>
<span class="comment">// =&gt; 2 neurons for the hidden layer</span>
<span class="comment">// =&gt; 1 neuron for the output layer</span>
<span class="comment">// =&gt; a learning rate == 0.005 (just get it doing some tests until satisfied)</span>
<span class="comment">// =&gt; 1000 learning steps (i.e. the network will be ready after 1000 training steps to adjust the synaptical weights</span>
<span class="comment">// =&gt; 0.1 as neural threshold (the threshold above which a neuron activates)</span>
<a name="_a0"></a><a class="code" href="classneuralpp_1_1NeuralNet.html" title="Main project&amp;#39;s class.">NeuralNet</a> net(2, 2, 1, 0.005, 1000, 0.1);
<span class="comment">// Initialize a training XML as a string in 'xml'</span>
NeuralNet::initXML(xml);
<span class="comment">// Build some training sets for the XML. The format is:</span>
<span class="comment">// "input1,input2,...,inputn;output1,output2,...,outputn</span>
<span class="comment">// The 'id' variable is passed as reference, starting from 0,</span>
<span class="comment">// and it's used to enumerate the sets in the XML file.</span>
xml += NeuralNet::XMLFromSet(<span class="keywordtype">id</span>, <span class="stringliteral">"2,3;5"</span>);
xml += NeuralNet::XMLFromSet(<span class="keywordtype">id</span>, <span class="stringliteral">"3,2;5"</span>);
xml += NeuralNet::XMLFromSet(<span class="keywordtype">id</span>, <span class="stringliteral">"6,2;8"</span>);
xml += NeuralNet::XMLFromSet(<span class="keywordtype">id</span>, <span class="stringliteral">"2,2;4"</span>);
xml += NeuralNet::XMLFromSet(<span class="keywordtype">id</span>, <span class="stringliteral">"1,2;3"</span>);
xml += NeuralNet::XMLFromSet(<span class="keywordtype">id</span>, <span class="stringliteral">"-1,-2;-3"</span>);
xml += NeuralNet::XMLFromSet(<span class="keywordtype">id</span>, <span class="stringliteral">"8,9;17"</span>);
xml += NeuralNet::XMLFromSet(<span class="keywordtype">id</span>, <span class="stringliteral">"10,10;20"</span>);
NeuralNet::closeXML(xml);
<span class="comment">// Save the XML string just created to a file</span>
ofstream out(<span class="stringliteral">"adder.xml"</span>);
out &lt;&lt; xml;
out.close();
cout &lt;&lt; <span class="stringliteral">"Training file adder.xml has been written\n"</span>;
<span class="comment">// Start the training from the XML file</span>
t1 = time(NULL);
cout &lt;&lt; <span class="stringliteral">"Training in progress - This may take a while...\n"</span>;
net.<a name="a1"></a><a class="code" href="classneuralpp_1_1NeuralNet.html#1c9e17437d41a7048611e21a3cc1c7dd" title="Train a network using a training set loaded from an XML file.">train</a>(<span class="stringliteral">"adder.xml"</span>, NeuralNet::file);
t2 = time(NULL);
<span class="comment">// Save the trained network to a binary file, that can be reloaded from any</span>
<span class="comment">// application that is going to use that network</span>
net.<a name="a2"></a><a class="code" href="classneuralpp_1_1NeuralNet.html#fdf94c276720c25e565cac834fe8a407" title="Save a trained neural network to a binary file.">save</a>(<span class="stringliteral">"adder.net"</span>);
cout &lt;&lt; <span class="stringliteral">"Network trained in "</span> &lt;&lt; (t2-t1) &lt;&lt; <span class="stringliteral">" seconds. You can use adder.net file now to load this network\n"</span>;
<span class="keywordflow">return</span> 0;
}
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@ -28,7 +29,7 @@
<tr><td class="indexkey"><a class="el" href="neural_09_09__exception_8hpp.html">neural++_exception.hpp</a> <a href="neural_09_09__exception_8hpp-source.html">[code]</a></td><td class="indexvalue"></td></tr>
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@ -12,6 +12,7 @@
<li><a href="namespaces.html"><span>Namespaces</span></a></li>
<li class="current"><a href="annotated.html"><span>Classes</span></a></li>
<li><a href="files.html"><span>Files</span></a></li>
<li><a href="examples.html"><span>Examples</span></a></li>
</ul>
</div>
<div class="tabs">
@ -59,7 +60,7 @@ Here is a list of all class members with links to the classes they belong to:
<p>
<h3><a class="anchor" name="index_e">- e -</a></h3><ul>
<li>elements
: <a class="el" href="classneuralpp_1_1Layer.html#855685c9da56b06b629e13a2f8c719ce">neuralpp::Layer</a>
: <a class="el" href="classneuralpp_1_1Layer.html#8188cb5c264e6021cee9979b968a0305">neuralpp::Layer</a>
<li>ElemPos()
: <a class="el" href="structCMarkup_1_1ElemPos.html#7ba7e4930d77275e80e38ea151b2807b">CMarkup::ElemPos</a>
<li>EncodeCharUTF16()
@ -72,17 +73,18 @@ Here is a list of all class members with links to the classes they belong to:
: <a class="el" href="structneuralpp_1_1netrecord.html#ab0149ed5ea0694e88213a07cd4427d1">neuralpp::netrecord</a>
, <a class="el" href="classneuralpp_1_1NeuralNet.html#4cb52dae7b43d03fac73afca7b9f3a51">neuralpp::NeuralNet</a>
<li>error()
: <a class="el" href="classneuralpp_1_1NeuralNet.html#0616c51404efaca2714e37dd7478997e">neuralpp::NeuralNet</a>
: <a class="el" href="classneuralpp_1_1NeuralNet.html#8a140d28e6dd4097470c7c138801ad01">neuralpp::NeuralNet</a>
<li>EscapeText()
: <a class="el" href="classCMarkup.html#ba91db9799ea46f2594a85f7026b6034">CMarkup</a>
<li>ex
: <a class="el" href="structneuralpp_1_1netrecord.html#dcc44fde3f67058d26ef2d5cbd0904e6">neuralpp::netrecord</a>
, <a class="el" href="classneuralpp_1_1NeuralNet.html#261f5f68fcc5be54250cfa03945266dd">neuralpp::NeuralNet</a>
<li>expect
: <a class="el" href="classneuralpp_1_1NeuralNet.html#a9e4ff43427f56663739c4c7450de8ee">neuralpp::NeuralNet</a>
<li>expected()
: <a class="el" href="classneuralpp_1_1NeuralNet.html#562dfe9fb8d73bf25a23ce608451d3aa">neuralpp::NeuralNet</a>
</ul>
</div>
<hr size="1"><address style="text-align: right;"><small>Generated on Sat Aug 15 02:56:02 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
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<img src="doxygen.png" alt="doxygen" align="middle" border="0"></a> 1.5.6 </small></address>
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@ -12,6 +12,7 @@
<li><a href="namespaces.html"><span>Namespaces</span></a></li>
<li class="current"><a href="annotated.html"><span>Classes</span></a></li>
<li><a href="files.html"><span>Files</span></a></li>
<li><a href="examples.html"><span>Examples</span></a></li>
</ul>
</div>
<div class="tabs">
@ -72,7 +73,7 @@ Here is a list of all class members with links to the classes they belong to:
: <a class="el" href="structCMarkup_1_1FilePos.html#d5d7584cf09fa60ef62f5c764e1ee158">CMarkup::FilePos</a>
</ul>
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<hr size="1"><address style="text-align: right;"><small>Generated on Sat Aug 15 02:56:02 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
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<img src="doxygen.png" alt="doxygen" align="middle" border="0"></a> 1.5.6 </small></address>
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@ -12,6 +12,7 @@
<li><a href="namespaces.html"><span>Namespaces</span></a></li>
<li class="current"><a href="annotated.html"><span>Classes</span></a></li>
<li><a href="files.html"><span>Files</span></a></li>
<li><a href="examples.html"><span>Examples</span></a></li>
</ul>
</div>
<div class="tabs">
@ -77,7 +78,7 @@ Here is a list of all class members with links to the classes they belong to:
<li>GetDeclaredEncoding()
: <a class="el" href="classCMarkup.html#1f2b3c176609588986004058a77afe27">CMarkup</a>
<li>getDelta()
: <a class="el" href="classneuralpp_1_1Synapsis.html#18f15b920609be8b818d43a0227aada5">neuralpp::Synapsis</a>
: <a class="el" href="classneuralpp_1_1Synapsis.html#00c8e9c0804662f2b3247d6dddb4ca6c">neuralpp::Synapsis</a>
<li>GetDoc()
: <a class="el" href="classCMarkup.html#04364a3697a67d5652b2259bd8b17889">CMarkup</a>
<li>GetDocFlags()
@ -86,18 +87,20 @@ Here is a list of all class members with links to the classes they belong to:
: <a class="el" href="classCMarkup.html#9dfbb66afa75291b5ed19b51e0f6357b">CMarkup</a>
<li>GetError()
: <a class="el" href="classCMarkup.html#15f1042ff13167216b741f360e88f649">CMarkup</a>
<li>getExpected()
: <a class="el" href="classneuralpp_1_1NeuralNet.html#51a1851ed07b85bec091c9053ae99cf7">neuralpp::NeuralNet</a>
<li>getIn()
: <a class="el" href="classneuralpp_1_1Synapsis.html#5ba8a93a5741f4855390eb8a46e99435">neuralpp::Synapsis</a>
: <a class="el" href="classneuralpp_1_1Synapsis.html#298fd3c7483ad572899fecec01ac8fdf">neuralpp::Synapsis</a>
<li>GetNodeType()
: <a class="el" href="classCMarkup.html#86a5f997b734d560b3b21c8ef89d3a57">CMarkup</a>
<li>getOut()
: <a class="el" href="classneuralpp_1_1Synapsis.html#61c9a04e03291a01f44520cef143cbdd">neuralpp::Synapsis</a>
: <a class="el" href="classneuralpp_1_1Synapsis.html#b46d876761a73a24db87f5a144a0e899">neuralpp::Synapsis</a>
<li>getOutput()
: <a class="el" href="classneuralpp_1_1NeuralNet.html#961dce8913264bf64c899dce4e25f810">neuralpp::NeuralNet</a>
<li>getOutputs()
: <a class="el" href="classneuralpp_1_1NeuralNet.html#a6b8bf3800b43b58843c65fc431207ae">neuralpp::NeuralNet</a>
: <a class="el" href="classneuralpp_1_1NeuralNet.html#e6d2215ecc8b560db2f6797db642191c">neuralpp::NeuralNet</a>
<li>getPrevDelta()
: <a class="el" href="classneuralpp_1_1Synapsis.html#2fe3e9ec97542f1476d8b9306aa09756">neuralpp::Synapsis</a>
: <a class="el" href="classneuralpp_1_1Synapsis.html#0148b9c8db870c928711168702ae51c5">neuralpp::Synapsis</a>
<li>getProp()
: <a class="el" href="classneuralpp_1_1Neuron.html#57c022f82213f662e2a263fc134a3fc9">neuralpp::Neuron</a>
<li>GetSize()
@ -106,11 +109,13 @@ Here is a list of all class members with links to the classes they belong to:
: <a class="el" href="classCMarkup.html#9d963c7234a4cecc16d9bd46c32ff87a">CMarkup</a>
<li>GetTagName()
: <a class="el" href="classCMarkup.html#0fcd179bb0ba35d6a262d571c1ef1004">CMarkup</a>
<li>getThreshold()
: <a class="el" href="classneuralpp_1_1NeuralNet.html#e08cdcf4b70f987700e553d9914f6179">neuralpp::NeuralNet</a>
<li>getWeight()
: <a class="el" href="classneuralpp_1_1Synapsis.html#aa79c16ec6b59949e5d2f75a3f10d530">neuralpp::Synapsis</a>
: <a class="el" href="classneuralpp_1_1Synapsis.html#bcbf7228632ff4d6bbb67703323d2db0">neuralpp::Synapsis</a>
</ul>
</div>
<hr size="1"><address style="text-align: right;"><small>Generated on Sat Aug 15 02:56:02 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
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<img src="doxygen.png" alt="doxygen" align="middle" border="0"></a> 1.5.6 </small></address>
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@ -12,6 +12,7 @@
<li><a href="namespaces.html"><span>Namespaces</span></a></li>
<li class="current"><a href="annotated.html"><span>Classes</span></a></li>
<li><a href="files.html"><span>Files</span></a></li>
<li><a href="examples.html"><span>Examples</span></a></li>
</ul>
</div>
<div class="tabs">
@ -64,7 +65,7 @@ Here is a list of all class members with links to the classes they belong to:
: <a class="el" href="structneuralpp_1_1netrecord.html#3c1728ac66c37f6ac85c404d4f55552e">neuralpp::netrecord</a>
</ul>
</div>
<hr size="1"><address style="text-align: right;"><small>Generated on Sat Aug 15 02:56:02 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
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<img src="doxygen.png" alt="doxygen" align="middle" border="0"></a> 1.5.6 </small></address>
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View file

@ -12,6 +12,7 @@
<li><a href="namespaces.html"><span>Namespaces</span></a></li>
<li class="current"><a href="annotated.html"><span>Classes</span></a></li>
<li><a href="files.html"><span>Files</span></a></li>
<li><a href="examples.html"><span>Examples</span></a></li>
</ul>
</div>
<div class="tabs">
@ -68,11 +69,11 @@ Here is a list of all class members with links to the classes they belong to:
: <a class="el" href="structCMarkup_1_1ElemPos.html#45534bddcab1f12a8452a070368488ca">CMarkup::ElemPos</a>
<li>in
: <a class="el" href="classneuralpp_1_1Synapsis.html#83d41c158054b08bd05051736e89a0ad">neuralpp::Synapsis</a>
, <a class="el" href="classneuralpp_1_1Neuron.html#ead827210fa18c2baae03927b2c798ff">neuralpp::Neuron</a>
, <a class="el" href="classneuralpp_1_1Neuron.html#bd07357465bb7b29bb344400e9e08710">neuralpp::Neuron</a>
<li>InitDocFlags()
: <a class="el" href="classCMarkup.html#6ce98f8685f47a0d5457ade12a9b500f">CMarkup</a>
<li>initXML()
: <a class="el" href="classneuralpp_1_1NeuralNet.html#45c7645d4affe65752d37cd230afba24">neuralpp::NeuralNet</a>
: <a class="el" href="classneuralpp_1_1NeuralNet.html#96da6712a72051cf34ad961761ef6e08">neuralpp::NeuralNet</a>
<li>input
: <a class="el" href="classneuralpp_1_1NeuralNet.html#e2b4e8405f9d25edab395d61502bdba9">neuralpp::NeuralNet</a>
<li>input_size
@ -89,6 +90,10 @@ Here is a list of all class members with links to the classes they belong to:
: <a class="el" href="classCMarkup.html#8f2a8484e2d4f8a27032f14818d96a66">CMarkup</a>
<li>IntoElem()
: <a class="el" href="classCMarkup.html#e6136fa65e4f1927fe763d011d3eb9a3">CMarkup</a>
<li>InvalidSynapticalWeightException()
: <a class="el" href="classneuralpp_1_1InvalidSynapticalWeightException.html#42e54de0ef9d9f711a483287f4f95916">neuralpp::InvalidSynapticalWeightException</a>
<li>InvalidXMLException()
: <a class="el" href="classneuralpp_1_1InvalidXMLException.html#10279e6f42a1ccb934afcfef2770c537">neuralpp::InvalidXMLException</a>
<li>iPos
: <a class="el" href="structCMarkup_1_1SavedPos.html#649563d0d7c11bf2fdebbc0dbe396321">CMarkup::SavedPos</a>
<li>IsEmptyElement()
@ -97,7 +102,7 @@ Here is a list of all class members with links to the classes they belong to:
: <a class="el" href="classCMarkup.html#f3a54e13b8565c2789c2c80aa2c9a563">CMarkup</a>
</ul>
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<hr size="1"><address style="text-align: right;"><small>Generated on Sat Aug 15 02:56:02 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
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<img src="doxygen.png" alt="doxygen" align="middle" border="0"></a> 1.5.6 </small></address>
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View file

@ -12,6 +12,7 @@
<li><a href="namespaces.html"><span>Namespaces</span></a></li>
<li class="current"><a href="annotated.html"><span>Classes</span></a></li>
<li><a href="files.html"><span>Files</span></a></li>
<li><a href="examples.html"><span>Examples</span></a></li>
</ul>
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<div class="tabs">
@ -62,7 +63,7 @@ Here is a list of all class members with links to the classes they belong to:
: <a class="el" href="classneuralpp_1_1NeuralNet.html#6bd7be443e46b2fdbf1da2edb8e611ab">neuralpp::NeuralNet</a>
, <a class="el" href="structneuralpp_1_1netrecord.html#a4f793a39a40144e811fef4d3d2d2b30">neuralpp::netrecord</a>
<li>Layer()
: <a class="el" href="classneuralpp_1_1Layer.html#609ed16b8d79dc384b01ba7d16b72bd1">neuralpp::Layer</a>
: <a class="el" href="classneuralpp_1_1Layer.html#d79f684523f8a6e086b962c8eef37623">neuralpp::Layer</a>
<li>Length()
: <a class="el" href="structCMarkup_1_1TokenPos.html#b033dc8e88a8f83748ff6c44df05bb04">CMarkup::TokenPos</a>
<li>Level()
@ -74,7 +75,7 @@ Here is a list of all class members with links to the classes they belong to:
: <a class="el" href="classCMarkup.html#c7604e24564eac2dce702f7fbaf430a6">CMarkup</a>
</ul>
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<hr size="1"><address style="text-align: right;"><small>Generated on Sat Aug 15 02:56:02 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
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@ -12,6 +12,7 @@
<li><a href="namespaces.html"><span>Namespaces</span></a></li>
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<li><a href="files.html"><span>Files</span></a></li>
<li><a href="examples.html"><span>Examples</span></a></li>
</ul>
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@ -167,10 +168,10 @@ Here is a list of all class members with links to the classes they belong to:
<li>MNT_WHITESPACE
: <a class="el" href="classCMarkup.html#a7f0377cbea81f5b932347af5fafab68840c4d18280cdc454e51b86168ed8c11">CMarkup</a>
<li>momentum()
: <a class="el" href="classneuralpp_1_1Synapsis.html#ecdb17182de791f7fdd417232e184350">neuralpp::Synapsis</a>
: <a class="el" href="classneuralpp_1_1Synapsis.html#cff10a022d4c021688e4df944c05d8bd">neuralpp::Synapsis</a>
</ul>
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<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
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<img src="doxygen.png" alt="doxygen" align="middle" border="0"></a> 1.5.6 </small></address>
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<li><a href="namespaces.html"><span>Namespaces</span></a></li>
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<li><a href="files.html"><span>Files</span></a></li>
<li><a href="examples.html"><span>Examples</span></a></li>
</ul>
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<div class="tabs">
@ -62,10 +63,16 @@ Here is a list of all class members with links to the classes they belong to:
: <a class="el" href="structCMarkup_1_1FilePos.html#f3c61a69075b838325939fd0e4955751">CMarkup::FilePos</a>
<li>nEndTagLen
: <a class="el" href="structCMarkup_1_1ElemPos.html#a53ebdfa2aecc621f9cdde9c247d3357">CMarkup::ElemPos</a>
<li>NetworkFileNotFoundException()
: <a class="el" href="classneuralpp_1_1NetworkFileNotFoundException.html#9603eebdb841f06c9b1007e65cba60f6">neuralpp::NetworkFileNotFoundException</a>
<li>NetworkFileWriteException()
: <a class="el" href="classneuralpp_1_1NetworkFileWriteException.html#83bc897b0ea11a384e0839a39e9fdb48">neuralpp::NetworkFileWriteException</a>
<li>NetworkIndexOutOfBoundsException()
: <a class="el" href="classneuralpp_1_1NetworkIndexOutOfBoundsException.html#07141d2225ea9f2d486e755a3660d594">neuralpp::NetworkIndexOutOfBoundsException</a>
<li>NeuralNet()
: <a class="el" href="classneuralpp_1_1NeuralNet.html#c79534c7c0dfb20d1d03be2ad7569b78">neuralpp::NeuralNet</a>
: <a class="el" href="classneuralpp_1_1NeuralNet.html#b4bfa407d28bb17abf7f735a049987d9">neuralpp::NeuralNet</a>
<li>Neuron()
: <a class="el" href="classneuralpp_1_1Neuron.html#f1bf19ec93174f60b368ee4a91b03f46">neuralpp::Neuron</a>
: <a class="el" href="classneuralpp_1_1Neuron.html#c9bd4f5f618fcf1adcebf1ab63ee0960">neuralpp::Neuron</a>
<li>nFailedChars
: <a class="el" href="structCMarkup_1_1ConvertEncoding.html#bfd8cc96d41531109b9301b4d28a695f">CMarkup::ConvertEncoding</a>
<li>nFileByteLen
@ -112,8 +119,8 @@ Here is a list of all class members with links to the classes they belong to:
<li>nSegs
: <a class="el" href="structCMarkup_1_1PosArray.html#0994a05167565499a77d9d9d09711029">CMarkup::PosArray</a>
<li>nSize
: <a class="el" href="structCMarkup_1_1PosArray.html#f7a261e70c4060b8ef5070c0a5e12092">CMarkup::PosArray</a>
, <a class="el" href="structCMarkup_1_1NodeStack.html#7031af9e6f3ceca049b5467b1fd7e478">CMarkup::NodeStack</a>
: <a class="el" href="structCMarkup_1_1NodeStack.html#7031af9e6f3ceca049b5467b1fd7e478">CMarkup::NodeStack</a>
, <a class="el" href="structCMarkup_1_1PosArray.html#f7a261e70c4060b8ef5070c0a5e12092">CMarkup::PosArray</a>
<li>nStart
: <a class="el" href="structCMarkup_1_1NodePos.html#c1939dd0ed1d2ecb35eb35bd2e88f69c">CMarkup::NodePos</a>
, <a class="el" href="structCMarkup_1_1ElemPos.html#37cbff8b4e0d5b086970efb1bc9b70fe">CMarkup::ElemPos</a>
@ -127,7 +134,7 @@ Here is a list of all class members with links to the classes they belong to:
: <a class="el" href="structCMarkup_1_1NodeStack.html#f3e08fa5dce853a6267da9f77ef3f986">CMarkup::NodeStack</a>
</ul>
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<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
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@ -12,6 +12,7 @@
<li><a href="namespaces.html"><span>Namespaces</span></a></li>
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<li><a href="files.html"><span>Files</span></a></li>
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</ul>
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@ -67,7 +68,7 @@ Here is a list of all class members with links to the classes they belong to:
, <a class="el" href="structCMarkup_1_1PosArray.html#6317965f42dadc70f55c99b547e5d83d">CMarkup::PosArray</a>
<li>out
: <a class="el" href="classneuralpp_1_1Synapsis.html#fb219e05038fa0da20db1082ab0500be">neuralpp::Synapsis</a>
, <a class="el" href="classneuralpp_1_1Neuron.html#82a4297f84d6403e52a8386d26117b4f">neuralpp::Neuron</a>
, <a class="el" href="classneuralpp_1_1Neuron.html#982aceef324b7764e778d5949720bc55">neuralpp::Neuron</a>
<li>OutOfElem()
: <a class="el" href="classCMarkup.html#012bca9ceaf157033a5697fa6ea92e45">CMarkup</a>
<li>output
@ -76,7 +77,7 @@ Here is a list of all class members with links to the classes they belong to:
: <a class="el" href="structneuralpp_1_1netrecord.html#95f2b0651dd3a0e5e7201ff354e401b4">neuralpp::netrecord</a>
</ul>
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<li><a href="namespaces.html"><span>Namespaces</span></a></li>
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<li><a href="files.html"><span>Files</span></a></li>
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</ul>
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@ -81,7 +82,7 @@ Here is a list of all class members with links to the classes they belong to:
<li>prop_val
: <a class="el" href="classneuralpp_1_1Neuron.html#da75259de98b1a893c736666af6bfdc3">neuralpp::Neuron</a>
<li>propagate()
: <a class="el" href="classneuralpp_1_1Neuron.html#8b0ca61cd0e047c8691ab39aae56dbda">neuralpp::Neuron</a>
: <a class="el" href="classneuralpp_1_1Neuron.html#928d9bf5aed600119c640779e4034f30">neuralpp::Neuron</a>
, <a class="el" href="classneuralpp_1_1Layer.html#fcfd306039dbaf91c9e2dcc8fc1f1ce1">neuralpp::Layer</a>
, <a class="el" href="classneuralpp_1_1NeuralNet.html#c129c180647362da963758bfd1ba6890">neuralpp::NeuralNet</a>
<li>pSegs
@ -89,12 +90,12 @@ Here is a list of all class members with links to the classes they belong to:
<li>pTable
: <a class="el" href="structCMarkup_1_1SavedPosMap.html#8ebb44e96f6781e5d1d044a18a3d989d">CMarkup::SavedPosMap</a>
<li>push_in()
: <a class="el" href="classneuralpp_1_1Neuron.html#583ada6e1dd3f2e113415b4d89196e62">neuralpp::Neuron</a>
: <a class="el" href="classneuralpp_1_1Neuron.html#4d252151c35839975838539d846d70be">neuralpp::Neuron</a>
<li>push_out()
: <a class="el" href="classneuralpp_1_1Neuron.html#bca65db84f56f9d40694bfbcd25812cb">neuralpp::Neuron</a>
: <a class="el" href="classneuralpp_1_1Neuron.html#2c0acb0e6d413c4e0fc9e7939da1a684">neuralpp::Neuron</a>
</ul>
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<hr size="1"><address style="text-align: right;"><small>Generated on Sat Aug 15 02:56:02 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
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@ -85,7 +86,7 @@ Here is a list of all class members with links to the classes they belong to:
: <a class="el" href="classCMarkup.html#dbab6d52d320eac695850f0b47e5b5ce">CMarkup</a>
</ul>
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<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
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@ -58,10 +59,10 @@
Here is a list of all class members with links to the classes they belong to:
<p>
<h3><a class="anchor" name="index_s">- s -</a></h3><ul>
<li>Save()
: <a class="el" href="classCMarkup.html#61b774f533449eeda7f3d78d8d69e4fb">CMarkup</a>
<li>save()
: <a class="el" href="classneuralpp_1_1NeuralNet.html#fdf94c276720c25e565cac834fe8a407">neuralpp::NeuralNet</a>
<li>Save()
: <a class="el" href="classCMarkup.html#61b774f533449eeda7f3d78d8d69e4fb">CMarkup</a>
<li>SavedPos()
: <a class="el" href="structCMarkup_1_1SavedPos.html#203b3a22eb86b1131985a6631e3d3c47">CMarkup::SavedPos</a>
<li>SavedPosMap()
@ -74,7 +75,6 @@ Here is a list of all class members with links to the classes they belong to:
: <a class="el" href="structCMarkup_1_1PosArray.html#0310976aa8e777cb84ab02ddbae8864c">CMarkup::PosArray</a>
<li>setActv()
: <a class="el" href="classneuralpp_1_1Neuron.html#ddf00ffef030b27ed11901aad08822bd">neuralpp::Neuron</a>
, <a class="el" href="classneuralpp_1_1Layer.html#98f79281b680b1d18fd91fa5794c0899">neuralpp::Layer</a>
<li>SetAttrib()
: <a class="el" href="classCMarkup.html#e358f67c104c9b02e93a8a33cd81093f">CMarkup</a>
<li>SetChildAttrib()
@ -82,7 +82,7 @@ Here is a list of all class members with links to the classes they belong to:
<li>SetChildData()
: <a class="el" href="classCMarkup.html#b2db581de961cbdf0004e9377029a8c7">CMarkup</a>
<li>SetData()
: <a class="el" href="classCMarkup.html#65f994e7c180c9e02cb8a3deb9cc1a32">CMarkup</a>
: <a class="el" href="classCMarkup.html#ce922c959d826b28f4ad2b279697238b">CMarkup</a>
<li>setDelta()
: <a class="el" href="classneuralpp_1_1Synapsis.html#429ad5b25930faf436a9d725582802e1">neuralpp::Synapsis</a>
<li>SetDoc()
@ -96,14 +96,14 @@ Here is a list of all class members with links to the classes they belong to:
<li>setExpected()
: <a class="el" href="classneuralpp_1_1NeuralNet.html#b6475762b7e9eab086befdc511f7c236">neuralpp::NeuralNet</a>
<li>setInput()
: <a class="el" href="classneuralpp_1_1NeuralNet.html#0de170e8ab561ad63d0739b4c4b74f68">neuralpp::NeuralNet</a>
: <a class="el" href="classneuralpp_1_1NeuralNet.html#405b32d2928344314ecf0469070b0f17">neuralpp::NeuralNet</a>
, <a class="el" href="classneuralpp_1_1Layer.html#88ceffc23f02a9dc24d4355767b7cca7">neuralpp::Layer</a>
<li>SetLevel()
: <a class="el" href="structCMarkup_1_1ElemPos.html#625d84902ebb86bda4d5c5720f00e885">CMarkup::ElemPos</a>
<li>SetMapSize()
: <a class="el" href="classCMarkup.html#834d5e280500d0f62cd6fdb53b834ebb">CMarkup</a>
<li>setProp()
: <a class="el" href="classneuralpp_1_1Neuron.html#aa6e58f073a76b3481fea9115a4e6ea6">neuralpp::Neuron</a>
, <a class="el" href="classneuralpp_1_1Layer.html#dbad95f635343a2998794113d7762cf7">neuralpp::Layer</a>
<li>SetStartTagLen()
: <a class="el" href="structCMarkup_1_1ElemPos.html#6f366b2f636e221db004bf44fd952912">CMarkup::ElemPos</a>
<li>setWeight()
@ -113,7 +113,7 @@ Here is a list of all class members with links to the classes they belong to:
<li>source
: <a class="el" href="classneuralpp_1_1NeuralNet.html#94c36c94060e785ea67a0014c4182f8f">neuralpp::NeuralNet</a>
<li>split()
: <a class="el" href="classneuralpp_1_1NeuralNet.html#e07af23ceb8666518da0c035bf1e0376">neuralpp::NeuralNet</a>
: <a class="el" href="classneuralpp_1_1NeuralNet.html#83c6555520856d5867752904349ab6ca">neuralpp::NeuralNet</a>
<li>SPM_CHILD
: <a class="el" href="structCMarkup_1_1SavedPos.html#28ed16429117003133c33fa8fcaa792437b333ca861ee132a96570e3261ed48f">CMarkup::SavedPos</a>
<li>SPM_LAST
@ -145,7 +145,7 @@ Here is a list of all class members with links to the classes they belong to:
<li>strToEncoding
: <a class="el" href="structCMarkup_1_1ConvertEncoding.html#cc2420305e7cfa6c9d18f7ce9daa4313">CMarkup::ConvertEncoding</a>
<li>Synapsis()
: <a class="el" href="classneuralpp_1_1Synapsis.html#b767332fdce81af25486b8969e5d2fb3">neuralpp::Synapsis</a>
: <a class="el" href="classneuralpp_1_1Synapsis.html#0729de9e737b9967421edcfc4b410bd8">neuralpp::Synapsis</a>
<li>synClear()
: <a class="el" href="classneuralpp_1_1Neuron.html#2e2ccb69277fc3d992a3a3f2360ed154">neuralpp::Neuron</a>
<li>synIn()
@ -154,7 +154,7 @@ Here is a list of all class members with links to the classes they belong to:
: <a class="el" href="classneuralpp_1_1Neuron.html#655f1637e1b754461413ac7fc2ffeebe">neuralpp::Neuron</a>
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<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
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@ -58,6 +59,10 @@
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<h3><a class="anchor" name="index_t">- t -</a></h3><ul>
<li>threshold
: <a class="el" href="classneuralpp_1_1NeuralNet.html#327dbfdd72b0a74293f8f29630525aa3">neuralpp::NeuralNet</a>
, <a class="el" href="classneuralpp_1_1Neuron.html#7b16632868821d73dedcb8edaf6dbbef">neuralpp::Neuron</a>
, <a class="el" href="classneuralpp_1_1Layer.html#02cf4efe1da02a7404d25375c85ed71f">neuralpp::Layer</a>
<li>TokenPos()
: <a class="el" href="structCMarkup_1_1TokenPos.html#797a3f5d9664c52971cf210166c3636a">CMarkup::TokenPos</a>
<li>Top()
@ -65,10 +70,10 @@ Here is a list of all class members with links to the classes they belong to:
<li>TopIndex()
: <a class="el" href="structCMarkup_1_1NodeStack.html#4e9aad88e12b7bbabdbb3fd65fc51585">CMarkup::NodeStack</a>
<li>train()
: <a class="el" href="classneuralpp_1_1NeuralNet.html#ead4bdef0602a5cadbe3beb685e01f5f">neuralpp::NeuralNet</a>
: <a class="el" href="classneuralpp_1_1NeuralNet.html#1c9e17437d41a7048611e21a3cc1c7dd">neuralpp::NeuralNet</a>
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: <a class="el" href="classCMarkup.html#8e6cb088e69b6078f5923b0940fd647c">CMarkup</a>
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@ -62,11 +63,17 @@ Here is a list of all class members with links to the classes they belong to:
: <a class="el" href="structneuralpp_1_1synrecord.html#81a7dbc97eecbf5bc85cac46373a78d2">neuralpp::synrecord</a>
<li>weight
: <a class="el" href="classneuralpp_1_1Synapsis.html#0bc523a8135ebbb5c0da932939d30ed7">neuralpp::Synapsis</a>
<li>what()
: <a class="el" href="classneuralpp_1_1InvalidSynapticalWeightException.html#8d374dd7e8363b2551ae6e306b11473a">neuralpp::InvalidSynapticalWeightException</a>
, <a class="el" href="classneuralpp_1_1NetworkIndexOutOfBoundsException.html#8b65d77cb375a0aa40d5a9ea692bd5c3">neuralpp::NetworkIndexOutOfBoundsException</a>
, <a class="el" href="classneuralpp_1_1InvalidXMLException.html#4a8b81678ed0c319e1715ab5ef9112da">neuralpp::InvalidXMLException</a>
, <a class="el" href="classneuralpp_1_1NetworkFileWriteException.html#c8802852cb38d5edf6f490ff3acb6078">neuralpp::NetworkFileWriteException</a>
, <a class="el" href="classneuralpp_1_1NetworkFileNotFoundException.html#24cde7729ab22d343f36e638cfc40702">neuralpp::NetworkFileNotFoundException</a>
<li>WriteTextFile()
: <a class="el" href="classCMarkup.html#983286cbcb7c4f9aa1f462ffb5dc641f">CMarkup</a>
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<li>x_WriteText()
: <a class="el" href="classCMarkup.html#f3b30bc5314bbc8d157dca6d924f4852">CMarkup</a>
<li>XMLFromSet()
: <a class="el" href="classneuralpp_1_1NeuralNet.html#4be31ecb0b543a192997bd83c6995ccb">neuralpp::NeuralNet</a>
: <a class="el" href="classneuralpp_1_1NeuralNet.html#0a2733037af912b3e6a10146e7b7172f">neuralpp::NeuralNet</a>
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@ -70,7 +71,7 @@ Here is a list of all class members with links to the classes they belong to:
: <a class="el" href="structCMarkup_1_1SavedPosMapArray.html#6be57f9ebe160aebb464957caa30ddd6">CMarkup::SavedPosMapArray</a>
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@ -46,7 +47,7 @@
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@ -83,7 +84,7 @@
: <a class="el" href="classCMarkup.html#3257cd5f249587254e816d12bd3b0e0d">CMarkup</a>
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@ -63,11 +64,11 @@
<li>ClearVirtualParent()
: <a class="el" href="structCMarkup_1_1ElemPos.html#b70cf4ad47e44a2d4c7f6c06a2ff0659">CMarkup::ElemPos</a>
<li>closeXML()
: <a class="el" href="classneuralpp_1_1NeuralNet.html#28b9966c5f197b8e86d57dd104aa32a6">neuralpp::NeuralNet</a>
: <a class="el" href="classneuralpp_1_1NeuralNet.html#e17732ed578bc4bd6032bfae58a5cf51">neuralpp::NeuralNet</a>
<li>CMarkup()
: <a class="el" href="classCMarkup.html#e4dc90b99846d35849bc323064fbafcf">CMarkup</a>
<li>commitChanges()
: <a class="el" href="classneuralpp_1_1NeuralNet.html#62695a82dfb1df758a44150921aec8e0">neuralpp::NeuralNet</a>
: <a class="el" href="classneuralpp_1_1NeuralNet.html#f697a8d9967ad8f03e5a16a42cd110c5">neuralpp::NeuralNet</a>
<li>ContentLen()
: <a class="el" href="structCMarkup_1_1ElemPos.html#9099635ab9239103aa930b2f1a456d2d">CMarkup::ElemPos</a>
<li>ConvertEncoding()
@ -76,7 +77,7 @@
: <a class="el" href="structCMarkup_1_1NodeStack.html#499a05e053b785df518fb0b6124fd0ee">CMarkup::NodeStack</a>
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<li><a href="examples.html"><span>Examples</span></a></li>
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@ -66,14 +67,14 @@
<li>EndTagLen()
: <a class="el" href="structCMarkup_1_1ElemPos.html#d9d0ad0c48a129555d1052e98e4f71bd">CMarkup::ElemPos</a>
<li>error()
: <a class="el" href="classneuralpp_1_1NeuralNet.html#0616c51404efaca2714e37dd7478997e">neuralpp::NeuralNet</a>
: <a class="el" href="classneuralpp_1_1NeuralNet.html#8a140d28e6dd4097470c7c138801ad01">neuralpp::NeuralNet</a>
<li>EscapeText()
: <a class="el" href="classCMarkup.html#ba91db9799ea46f2594a85f7026b6034">CMarkup</a>
<li>expected()
: <a class="el" href="classneuralpp_1_1NeuralNet.html#562dfe9fb8d73bf25a23ce608451d3aa">neuralpp::NeuralNet</a>
</ul>
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<hr size="1"><address style="text-align: right;"><small>Generated on Sat Aug 15 02:56:02 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
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@ -67,7 +68,7 @@
: <a class="el" href="classCMarkup.html#e29573627f9b0cdc0d7152ff749ba407">CMarkup</a>
</ul>
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<hr size="1"><address style="text-align: right;"><small>Generated on Sat Aug 15 02:56:02 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
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<div class="tabs">
@ -76,7 +77,7 @@
<li>GetDeclaredEncoding()
: <a class="el" href="classCMarkup.html#1f2b3c176609588986004058a77afe27">CMarkup</a>
<li>getDelta()
: <a class="el" href="classneuralpp_1_1Synapsis.html#18f15b920609be8b818d43a0227aada5">neuralpp::Synapsis</a>
: <a class="el" href="classneuralpp_1_1Synapsis.html#00c8e9c0804662f2b3247d6dddb4ca6c">neuralpp::Synapsis</a>
<li>GetDoc()
: <a class="el" href="classCMarkup.html#04364a3697a67d5652b2259bd8b17889">CMarkup</a>
<li>GetDocFlags()
@ -85,18 +86,20 @@
: <a class="el" href="classCMarkup.html#9dfbb66afa75291b5ed19b51e0f6357b">CMarkup</a>
<li>GetError()
: <a class="el" href="classCMarkup.html#15f1042ff13167216b741f360e88f649">CMarkup</a>
<li>getExpected()
: <a class="el" href="classneuralpp_1_1NeuralNet.html#51a1851ed07b85bec091c9053ae99cf7">neuralpp::NeuralNet</a>
<li>getIn()
: <a class="el" href="classneuralpp_1_1Synapsis.html#5ba8a93a5741f4855390eb8a46e99435">neuralpp::Synapsis</a>
: <a class="el" href="classneuralpp_1_1Synapsis.html#298fd3c7483ad572899fecec01ac8fdf">neuralpp::Synapsis</a>
<li>GetNodeType()
: <a class="el" href="classCMarkup.html#86a5f997b734d560b3b21c8ef89d3a57">CMarkup</a>
<li>getOut()
: <a class="el" href="classneuralpp_1_1Synapsis.html#61c9a04e03291a01f44520cef143cbdd">neuralpp::Synapsis</a>
: <a class="el" href="classneuralpp_1_1Synapsis.html#b46d876761a73a24db87f5a144a0e899">neuralpp::Synapsis</a>
<li>getOutput()
: <a class="el" href="classneuralpp_1_1NeuralNet.html#961dce8913264bf64c899dce4e25f810">neuralpp::NeuralNet</a>
<li>getOutputs()
: <a class="el" href="classneuralpp_1_1NeuralNet.html#a6b8bf3800b43b58843c65fc431207ae">neuralpp::NeuralNet</a>
: <a class="el" href="classneuralpp_1_1NeuralNet.html#e6d2215ecc8b560db2f6797db642191c">neuralpp::NeuralNet</a>
<li>getPrevDelta()
: <a class="el" href="classneuralpp_1_1Synapsis.html#2fe3e9ec97542f1476d8b9306aa09756">neuralpp::Synapsis</a>
: <a class="el" href="classneuralpp_1_1Synapsis.html#0148b9c8db870c928711168702ae51c5">neuralpp::Synapsis</a>
<li>getProp()
: <a class="el" href="classneuralpp_1_1Neuron.html#57c022f82213f662e2a263fc134a3fc9">neuralpp::Neuron</a>
<li>GetSize()
@ -105,11 +108,13 @@
: <a class="el" href="classCMarkup.html#9d963c7234a4cecc16d9bd46c32ff87a">CMarkup</a>
<li>GetTagName()
: <a class="el" href="classCMarkup.html#0fcd179bb0ba35d6a262d571c1ef1004">CMarkup</a>
<li>getThreshold()
: <a class="el" href="classneuralpp_1_1NeuralNet.html#e08cdcf4b70f987700e553d9914f6179">neuralpp::NeuralNet</a>
<li>getWeight()
: <a class="el" href="classneuralpp_1_1Synapsis.html#aa79c16ec6b59949e5d2f75a3f10d530">neuralpp::Synapsis</a>
: <a class="el" href="classneuralpp_1_1Synapsis.html#bcbf7228632ff4d6bbb67703323d2db0">neuralpp::Synapsis</a>
</ul>
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<hr size="1"><address style="text-align: right;"><small>Generated on Sat Aug 15 02:56:02 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
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<li><a href="examples.html"><span>Examples</span></a></li>
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<div class="tabs">
@ -60,7 +61,7 @@
<li>InitDocFlags()
: <a class="el" href="classCMarkup.html#6ce98f8685f47a0d5457ade12a9b500f">CMarkup</a>
<li>initXML()
: <a class="el" href="classneuralpp_1_1NeuralNet.html#45c7645d4affe65752d37cd230afba24">neuralpp::NeuralNet</a>
: <a class="el" href="classneuralpp_1_1NeuralNet.html#96da6712a72051cf34ad961761ef6e08">neuralpp::NeuralNet</a>
<li>InsertChildElem()
: <a class="el" href="classCMarkup.html#91c3a9a4a47a3c8c9e184d9a6ee7f97a">CMarkup</a>
<li>InsertChildSubDoc()
@ -73,13 +74,17 @@
: <a class="el" href="classCMarkup.html#8f2a8484e2d4f8a27032f14818d96a66">CMarkup</a>
<li>IntoElem()
: <a class="el" href="classCMarkup.html#e6136fa65e4f1927fe763d011d3eb9a3">CMarkup</a>
<li>InvalidSynapticalWeightException()
: <a class="el" href="classneuralpp_1_1InvalidSynapticalWeightException.html#42e54de0ef9d9f711a483287f4f95916">neuralpp::InvalidSynapticalWeightException</a>
<li>InvalidXMLException()
: <a class="el" href="classneuralpp_1_1InvalidXMLException.html#10279e6f42a1ccb934afcfef2770c537">neuralpp::InvalidXMLException</a>
<li>IsEmptyElement()
: <a class="el" href="structCMarkup_1_1ElemPos.html#97093aa0ddbd691dd00c91c945a3e98a">CMarkup::ElemPos</a>
<li>IsWellFormed()
: <a class="el" href="classCMarkup.html#f3a54e13b8565c2789c2c80aa2c9a563">CMarkup</a>
</ul>
</div>
<hr size="1"><address style="text-align: right;"><small>Generated on Sat Aug 15 02:56:02 2009 for Neural++ by&nbsp;
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@ -58,7 +59,7 @@
<p>
<h3><a class="anchor" name="index_l">- l -</a></h3><ul>
<li>Layer()
: <a class="el" href="classneuralpp_1_1Layer.html#fb08bddd85d36570dabfe915461f07c5">neuralpp::Layer</a>
: <a class="el" href="classneuralpp_1_1Layer.html#a235767701b5e9dcf28c5e9e0d04cb0b">neuralpp::Layer</a>
<li>Length()
: <a class="el" href="structCMarkup_1_1TokenPos.html#b033dc8e88a8f83748ff6c44df05bb04">CMarkup::TokenPos</a>
<li>Level()
@ -70,7 +71,7 @@
: <a class="el" href="classCMarkup.html#c7604e24564eac2dce702f7fbaf430a6">CMarkup</a>
</ul>
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<hr size="1"><address style="text-align: right;"><small>Generated on Sat Aug 15 02:56:02 2009 for Neural++ by&nbsp;
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<li><a href="examples.html"><span>Examples</span></a></li>
</ul>
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<div class="tabs">
@ -62,10 +63,10 @@
<li>MCD_CSTR()
: <a class="el" href="structMCD__CSTR.html#527942329419b01535431646e136eaa1">MCD_CSTR</a>
<li>momentum()
: <a class="el" href="classneuralpp_1_1Synapsis.html#ecdb17182de791f7fdd417232e184350">neuralpp::Synapsis</a>
: <a class="el" href="classneuralpp_1_1Synapsis.html#cff10a022d4c021688e4df944c05d8bd">neuralpp::Synapsis</a>
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<div class="tabs">
@ -57,21 +58,27 @@
&nbsp;
<p>
<h3><a class="anchor" name="index_n">- n -</a></h3><ul>
<li>NetworkFileNotFoundException()
: <a class="el" href="classneuralpp_1_1NetworkFileNotFoundException.html#9603eebdb841f06c9b1007e65cba60f6">neuralpp::NetworkFileNotFoundException</a>
<li>NetworkFileWriteException()
: <a class="el" href="classneuralpp_1_1NetworkFileWriteException.html#83bc897b0ea11a384e0839a39e9fdb48">neuralpp::NetworkFileWriteException</a>
<li>NetworkIndexOutOfBoundsException()
: <a class="el" href="classneuralpp_1_1NetworkIndexOutOfBoundsException.html#07141d2225ea9f2d486e755a3660d594">neuralpp::NetworkIndexOutOfBoundsException</a>
<li>NeuralNet()
: <a class="el" href="classneuralpp_1_1NeuralNet.html#92b145f2f6f00bf1ba645ce2235882c2">neuralpp::NeuralNet</a>
<li>Neuron()
: <a class="el" href="classneuralpp_1_1Neuron.html#9863a08b73bc97c8b514aca6c580ff7b">neuralpp::Neuron</a>
: <a class="el" href="classneuralpp_1_1Neuron.html#d15e96b0316d880953288cc6e2550bec">neuralpp::Neuron</a>
<li>nIn()
: <a class="el" href="classneuralpp_1_1Neuron.html#ad97f1a082d5f969eb4c69ab454ecfbb">neuralpp::Neuron</a>
<li>NodePos()
: <a class="el" href="structCMarkup_1_1NodePos.html#81589c934561c891174be880864053b6">CMarkup::NodePos</a>
: <a class="el" href="structCMarkup_1_1NodePos.html#aaecb8354ffd5605e80432377fa2ac4c">CMarkup::NodePos</a>
<li>NodeStack()
: <a class="el" href="structCMarkup_1_1NodeStack.html#de0c540ed4a133345e7c8ec6e05b0b11">CMarkup::NodeStack</a>
<li>nOut()
: <a class="el" href="classneuralpp_1_1Neuron.html#fe458021e3b20d58dc608fb94ae2135b">neuralpp::Neuron</a>
</ul>
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@ -68,7 +69,7 @@
: <a class="el" href="classCMarkup.html#012bca9ceaf157033a5697fa6ea92e45">CMarkup</a>
</ul>
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<li><a href="namespaces.html"><span>Namespaces</span></a></li>
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</ul>
</div>
<div class="tabs">
@ -62,14 +63,14 @@
<li>propagate()
: <a class="el" href="classneuralpp_1_1NeuralNet.html#c129c180647362da963758bfd1ba6890">neuralpp::NeuralNet</a>
, <a class="el" href="classneuralpp_1_1Layer.html#fcfd306039dbaf91c9e2dcc8fc1f1ce1">neuralpp::Layer</a>
, <a class="el" href="classneuralpp_1_1Neuron.html#8b0ca61cd0e047c8691ab39aae56dbda">neuralpp::Neuron</a>
, <a class="el" href="classneuralpp_1_1Neuron.html#928d9bf5aed600119c640779e4034f30">neuralpp::Neuron</a>
<li>push_in()
: <a class="el" href="classneuralpp_1_1Neuron.html#583ada6e1dd3f2e113415b4d89196e62">neuralpp::Neuron</a>
: <a class="el" href="classneuralpp_1_1Neuron.html#4d252151c35839975838539d846d70be">neuralpp::Neuron</a>
<li>push_out()
: <a class="el" href="classneuralpp_1_1Neuron.html#bca65db84f56f9d40694bfbcd25812cb">neuralpp::Neuron</a>
: <a class="el" href="classneuralpp_1_1Neuron.html#2c0acb0e6d413c4e0fc9e7939da1a684">neuralpp::Neuron</a>
</ul>
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<li><a href="examples.html"><span>Examples</span></a></li>
</ul>
</div>
<div class="tabs">
@ -82,7 +83,7 @@
: <a class="el" href="classCMarkup.html#dbab6d52d320eac695850f0b47e5b5ce">CMarkup</a>
</ul>
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@ -57,10 +58,10 @@
&nbsp;
<p>
<h3><a class="anchor" name="index_s">- s -</a></h3><ul>
<li>Save()
: <a class="el" href="classCMarkup.html#61b774f533449eeda7f3d78d8d69e4fb">CMarkup</a>
<li>save()
: <a class="el" href="classneuralpp_1_1NeuralNet.html#fdf94c276720c25e565cac834fe8a407">neuralpp::NeuralNet</a>
<li>Save()
: <a class="el" href="classCMarkup.html#61b774f533449eeda7f3d78d8d69e4fb">CMarkup</a>
<li>SavedPos()
: <a class="el" href="structCMarkup_1_1SavedPos.html#203b3a22eb86b1131985a6631e3d3c47">CMarkup::SavedPos</a>
<li>SavedPosMap()
@ -73,7 +74,6 @@
: <a class="el" href="structCMarkup_1_1PosArray.html#0310976aa8e777cb84ab02ddbae8864c">CMarkup::PosArray</a>
<li>setActv()
: <a class="el" href="classneuralpp_1_1Neuron.html#ddf00ffef030b27ed11901aad08822bd">neuralpp::Neuron</a>
, <a class="el" href="classneuralpp_1_1Layer.html#98f79281b680b1d18fd91fa5794c0899">neuralpp::Layer</a>
<li>SetAttrib()
: <a class="el" href="classCMarkup.html#e358f67c104c9b02e93a8a33cd81093f">CMarkup</a>
<li>SetChildAttrib()
@ -81,7 +81,7 @@
<li>SetChildData()
: <a class="el" href="classCMarkup.html#b2db581de961cbdf0004e9377029a8c7">CMarkup</a>
<li>SetData()
: <a class="el" href="classCMarkup.html#65f994e7c180c9e02cb8a3deb9cc1a32">CMarkup</a>
: <a class="el" href="classCMarkup.html#ce922c959d826b28f4ad2b279697238b">CMarkup</a>
<li>setDelta()
: <a class="el" href="classneuralpp_1_1Synapsis.html#429ad5b25930faf436a9d725582802e1">neuralpp::Synapsis</a>
<li>SetDoc()
@ -95,14 +95,14 @@
<li>setExpected()
: <a class="el" href="classneuralpp_1_1NeuralNet.html#b6475762b7e9eab086befdc511f7c236">neuralpp::NeuralNet</a>
<li>setInput()
: <a class="el" href="classneuralpp_1_1NeuralNet.html#0de170e8ab561ad63d0739b4c4b74f68">neuralpp::NeuralNet</a>
: <a class="el" href="classneuralpp_1_1NeuralNet.html#405b32d2928344314ecf0469070b0f17">neuralpp::NeuralNet</a>
, <a class="el" href="classneuralpp_1_1Layer.html#88ceffc23f02a9dc24d4355767b7cca7">neuralpp::Layer</a>
<li>SetLevel()
: <a class="el" href="structCMarkup_1_1ElemPos.html#625d84902ebb86bda4d5c5720f00e885">CMarkup::ElemPos</a>
<li>SetMapSize()
: <a class="el" href="classCMarkup.html#834d5e280500d0f62cd6fdb53b834ebb">CMarkup</a>
<li>setProp()
: <a class="el" href="classneuralpp_1_1Neuron.html#aa6e58f073a76b3481fea9115a4e6ea6">neuralpp::Neuron</a>
, <a class="el" href="classneuralpp_1_1Layer.html#dbad95f635343a2998794113d7762cf7">neuralpp::Layer</a>
<li>SetStartTagLen()
: <a class="el" href="structCMarkup_1_1ElemPos.html#6f366b2f636e221db004bf44fd952912">CMarkup::ElemPos</a>
<li>setWeight()
@ -110,7 +110,7 @@
<li>size()
: <a class="el" href="classneuralpp_1_1Layer.html#7ca71ed62fbe9c1e9c0fb6a8dcaf76f0">neuralpp::Layer</a>
<li>split()
: <a class="el" href="classneuralpp_1_1NeuralNet.html#e07af23ceb8666518da0c035bf1e0376">neuralpp::NeuralNet</a>
: <a class="el" href="classneuralpp_1_1NeuralNet.html#83c6555520856d5867752904349ab6ca">neuralpp::NeuralNet</a>
<li>StartAfter()
: <a class="el" href="structCMarkup_1_1ElemPos.html#e1e21b6e27db22eda6178898d2aa42d3">CMarkup::ElemPos</a>
<li>StartContent()
@ -120,7 +120,7 @@
<li>StrNIACmp()
: <a class="el" href="structCMarkup_1_1TokenPos.html#c3a37f7294cd763aed0f37749095d3db">CMarkup::TokenPos</a>
<li>Synapsis()
: <a class="el" href="classneuralpp_1_1Synapsis.html#0729de9e737b9967421edcfc4b410bd8">neuralpp::Synapsis</a>
: <a class="el" href="classneuralpp_1_1Synapsis.html#b767332fdce81af25486b8969e5d2fb3">neuralpp::Synapsis</a>
<li>synClear()
: <a class="el" href="classneuralpp_1_1Neuron.html#2e2ccb69277fc3d992a3a3f2360ed154">neuralpp::Neuron</a>
<li>synIn()
@ -129,7 +129,7 @@
: <a class="el" href="classneuralpp_1_1Neuron.html#655f1637e1b754461413ac7fc2ffeebe">neuralpp::Neuron</a>
</ul>
</div>
<hr size="1"><address style="text-align: right;"><small>Generated on Sat Aug 15 02:56:02 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<a href="http://www.doxygen.org/index.html">
<img src="doxygen.png" alt="doxygen" align="middle" border="0"></a> 1.5.6 </small></address>
</body>

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@ -12,6 +12,7 @@
<li><a href="namespaces.html"><span>Namespaces</span></a></li>
<li class="current"><a href="annotated.html"><span>Classes</span></a></li>
<li><a href="files.html"><span>Files</span></a></li>
<li><a href="examples.html"><span>Examples</span></a></li>
</ul>
</div>
<div class="tabs">
@ -64,10 +65,10 @@
<li>TopIndex()
: <a class="el" href="structCMarkup_1_1NodeStack.html#4e9aad88e12b7bbabdbb3fd65fc51585">CMarkup::NodeStack</a>
<li>train()
: <a class="el" href="classneuralpp_1_1NeuralNet.html#ead4bdef0602a5cadbe3beb685e01f5f">neuralpp::NeuralNet</a>
: <a class="el" href="classneuralpp_1_1NeuralNet.html#1c9e17437d41a7048611e21a3cc1c7dd">neuralpp::NeuralNet</a>
</ul>
</div>
<hr size="1"><address style="text-align: right;"><small>Generated on Sat Aug 15 02:56:02 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<a href="http://www.doxygen.org/index.html">
<img src="doxygen.png" alt="doxygen" align="middle" border="0"></a> 1.5.6 </small></address>
</body>

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@ -12,6 +12,7 @@
<li><a href="namespaces.html"><span>Namespaces</span></a></li>
<li class="current"><a href="annotated.html"><span>Classes</span></a></li>
<li><a href="files.html"><span>Files</span></a></li>
<li><a href="examples.html"><span>Examples</span></a></li>
</ul>
</div>
<div class="tabs">
@ -71,7 +72,7 @@
: <a class="el" href="classCMarkup.html#8e6cb088e69b6078f5923b0940fd647c">CMarkup</a>
</ul>
</div>
<hr size="1"><address style="text-align: right;"><small>Generated on Sat Aug 15 02:56:02 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<a href="http://www.doxygen.org/index.html">
<img src="doxygen.png" alt="doxygen" align="middle" border="0"></a> 1.5.6 </small></address>
</body>

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@ -12,6 +12,7 @@
<li><a href="namespaces.html"><span>Namespaces</span></a></li>
<li class="current"><a href="annotated.html"><span>Classes</span></a></li>
<li><a href="files.html"><span>Files</span></a></li>
<li><a href="examples.html"><span>Examples</span></a></li>
</ul>
</div>
<div class="tabs">
@ -57,11 +58,17 @@
&nbsp;
<p>
<h3><a class="anchor" name="index_w">- w -</a></h3><ul>
<li>what()
: <a class="el" href="classneuralpp_1_1NetworkFileNotFoundException.html#24cde7729ab22d343f36e638cfc40702">neuralpp::NetworkFileNotFoundException</a>
, <a class="el" href="classneuralpp_1_1NetworkFileWriteException.html#c8802852cb38d5edf6f490ff3acb6078">neuralpp::NetworkFileWriteException</a>
, <a class="el" href="classneuralpp_1_1InvalidSynapticalWeightException.html#8d374dd7e8363b2551ae6e306b11473a">neuralpp::InvalidSynapticalWeightException</a>
, <a class="el" href="classneuralpp_1_1NetworkIndexOutOfBoundsException.html#8b65d77cb375a0aa40d5a9ea692bd5c3">neuralpp::NetworkIndexOutOfBoundsException</a>
, <a class="el" href="classneuralpp_1_1InvalidXMLException.html#4a8b81678ed0c319e1715ab5ef9112da">neuralpp::InvalidXMLException</a>
<li>WriteTextFile()
: <a class="el" href="classCMarkup.html#983286cbcb7c4f9aa1f462ffb5dc641f">CMarkup</a>
</ul>
</div>
<hr size="1"><address style="text-align: right;"><small>Generated on Sat Aug 15 02:56:02 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<a href="http://www.doxygen.org/index.html">
<img src="doxygen.png" alt="doxygen" align="middle" border="0"></a> 1.5.6 </small></address>
</body>

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@ -12,6 +12,7 @@
<li><a href="namespaces.html"><span>Namespaces</span></a></li>
<li class="current"><a href="annotated.html"><span>Classes</span></a></li>
<li><a href="files.html"><span>Files</span></a></li>
<li><a href="examples.html"><span>Examples</span></a></li>
</ul>
</div>
<div class="tabs">
@ -160,10 +161,10 @@
<li>x_WriteText()
: <a class="el" href="classCMarkup.html#f3b30bc5314bbc8d157dca6d924f4852">CMarkup</a>
<li>XMLFromSet()
: <a class="el" href="classneuralpp_1_1NeuralNet.html#4be31ecb0b543a192997bd83c6995ccb">neuralpp::NeuralNet</a>
: <a class="el" href="classneuralpp_1_1NeuralNet.html#0a2733037af912b3e6a10146e7b7172f">neuralpp::NeuralNet</a>
</ul>
</div>
<hr size="1"><address style="text-align: right;"><small>Generated on Sat Aug 15 02:56:02 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<a href="http://www.doxygen.org/index.html">
<img src="doxygen.png" alt="doxygen" align="middle" border="0"></a> 1.5.6 </small></address>
</body>

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@ -12,6 +12,7 @@
<li><a href="namespaces.html"><span>Namespaces</span></a></li>
<li class="current"><a href="annotated.html"><span>Classes</span></a></li>
<li><a href="files.html"><span>Files</span></a></li>
<li><a href="examples.html"><span>Examples</span></a></li>
</ul>
</div>
<div class="tabs">
@ -69,7 +70,7 @@
: <a class="el" href="structCMarkup_1_1SavedPosMapArray.html#6be57f9ebe160aebb464957caa30ddd6">CMarkup::SavedPosMapArray</a>
</ul>
</div>
<hr size="1"><address style="text-align: right;"><small>Generated on Sat Aug 15 02:56:02 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<a href="http://www.doxygen.org/index.html">
<img src="doxygen.png" alt="doxygen" align="middle" border="0"></a> 1.5.6 </small></address>
</body>

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@ -12,6 +12,7 @@
<li><a href="namespaces.html"><span>Namespaces</span></a></li>
<li class="current"><a href="annotated.html"><span>Classes</span></a></li>
<li><a href="files.html"><span>Files</span></a></li>
<li><a href="examples.html"><span>Examples</span></a></li>
</ul>
</div>
<div class="tabs">
@ -44,6 +45,7 @@
<li><a href="#index_p"><span>p</span></a></li>
<li><a href="#index_r"><span>r</span></a></li>
<li><a href="#index_s"><span>s</span></a></li>
<li><a href="#index_t"><span>t</span></a></li>
<li><a href="#index_u"><span>u</span></a></li>
<li><a href="#index_w"><span>w</span></a></li>
</ul>
@ -71,13 +73,14 @@
</ul>
<h3><a class="anchor" name="index_e">- e -</a></h3><ul>
<li>elements
: <a class="el" href="classneuralpp_1_1Layer.html#855685c9da56b06b629e13a2f8c719ce">neuralpp::Layer</a>
: <a class="el" href="classneuralpp_1_1Layer.html#8188cb5c264e6021cee9979b968a0305">neuralpp::Layer</a>
<li>epochs
: <a class="el" href="classneuralpp_1_1NeuralNet.html#4cb52dae7b43d03fac73afca7b9f3a51">neuralpp::NeuralNet</a>
, <a class="el" href="structneuralpp_1_1netrecord.html#ab0149ed5ea0694e88213a07cd4427d1">neuralpp::netrecord</a>
<li>ex
: <a class="el" href="classneuralpp_1_1NeuralNet.html#261f5f68fcc5be54250cfa03945266dd">neuralpp::NeuralNet</a>
, <a class="el" href="structneuralpp_1_1netrecord.html#dcc44fde3f67058d26ef2d5cbd0904e6">neuralpp::netrecord</a>
: <a class="el" href="structneuralpp_1_1netrecord.html#dcc44fde3f67058d26ef2d5cbd0904e6">neuralpp::netrecord</a>
<li>expect
: <a class="el" href="classneuralpp_1_1NeuralNet.html#a9e4ff43427f56663739c4c7450de8ee">neuralpp::NeuralNet</a>
</ul>
<h3><a class="anchor" name="index_f">- f -</a></h3><ul>
<li>fp
@ -100,7 +103,7 @@
: <a class="el" href="structCMarkup_1_1ElemPos.html#45534bddcab1f12a8452a070368488ca">CMarkup::ElemPos</a>
<li>in
: <a class="el" href="classneuralpp_1_1Synapsis.html#83d41c158054b08bd05051736e89a0ad">neuralpp::Synapsis</a>
, <a class="el" href="classneuralpp_1_1Neuron.html#ead827210fa18c2baae03927b2c798ff">neuralpp::Neuron</a>
, <a class="el" href="classneuralpp_1_1Neuron.html#bd07357465bb7b29bb344400e9e08710">neuralpp::Neuron</a>
<li>input
: <a class="el" href="classneuralpp_1_1NeuralNet.html#e2b4e8405f9d25edab395d61502bdba9">neuralpp::NeuralNet</a>
<li>input_size
@ -201,7 +204,7 @@
<h3><a class="anchor" name="index_o">- o -</a></h3><ul>
<li>out
: <a class="el" href="classneuralpp_1_1Synapsis.html#fb219e05038fa0da20db1082ab0500be">neuralpp::Synapsis</a>
, <a class="el" href="classneuralpp_1_1Neuron.html#82a4297f84d6403e52a8386d26117b4f">neuralpp::Neuron</a>
, <a class="el" href="classneuralpp_1_1Neuron.html#982aceef324b7764e778d5949720bc55">neuralpp::Neuron</a>
<li>output
: <a class="el" href="classneuralpp_1_1NeuralNet.html#fa9b2dbcbb39d0fc70f790ac24069a74">neuralpp::NeuralNet</a>
<li>output_size
@ -247,6 +250,12 @@
<li>strToEncoding
: <a class="el" href="structCMarkup_1_1ConvertEncoding.html#cc2420305e7cfa6c9d18f7ce9daa4313">CMarkup::ConvertEncoding</a>
</ul>
<h3><a class="anchor" name="index_t">- t -</a></h3><ul>
<li>threshold
: <a class="el" href="classneuralpp_1_1NeuralNet.html#327dbfdd72b0a74293f8f29630525aa3">neuralpp::NeuralNet</a>
, <a class="el" href="classneuralpp_1_1Layer.html#02cf4efe1da02a7404d25375c85ed71f">neuralpp::Layer</a>
, <a class="el" href="classneuralpp_1_1Neuron.html#7b16632868821d73dedcb8edaf6dbbef">neuralpp::Neuron</a>
</ul>
<h3><a class="anchor" name="index_u">- u -</a></h3><ul>
<li>update_weights
: <a class="el" href="classneuralpp_1_1Layer.html#c023a15a16353d0b4f44060a159f550f">neuralpp::Layer</a>
@ -258,7 +267,7 @@
: <a class="el" href="classneuralpp_1_1Synapsis.html#0bc523a8135ebbb5c0da932939d30ed7">neuralpp::Synapsis</a>
</ul>
</div>
<hr size="1"><address style="text-align: right;"><small>Generated on Sat Aug 15 02:56:02 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<a href="http://www.doxygen.org/index.html">
<img src="doxygen.png" alt="doxygen" align="middle" border="0"></a> 1.5.6 </small></address>
</body>

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@ -12,6 +12,7 @@
<li><a href="namespaces.html"><span>Namespaces</span></a></li>
<li><a href="annotated.html"><span>Classes</span></a></li>
<li class="current"><a href="files.html"><span>Files</span></a></li>
<li><a href="examples.html"><span>Examples</span></a></li>
</ul>
</div>
<div class="tabs">
@ -145,7 +146,7 @@ Here is a list of all file members with links to the files they belong to:
: <a class="el" href="neural_09_09_8hpp.html#839a9222721835f53c5b248241f535f4">neural++.hpp</a>
</ul>
</div>
<hr size="1"><address style="text-align: right;"><small>Generated on Sat Aug 15 02:56:02 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<a href="http://www.doxygen.org/index.html">
<img src="doxygen.png" alt="doxygen" align="middle" border="0"></a> 1.5.6 </small></address>
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@ -12,6 +12,7 @@
<li><a href="namespaces.html"><span>Namespaces</span></a></li>
<li><a href="annotated.html"><span>Classes</span></a></li>
<li class="current"><a href="files.html"><span>Files</span></a></li>
<li><a href="examples.html"><span>Examples</span></a></li>
</ul>
</div>
<div class="tabs">
@ -145,7 +146,7 @@
: <a class="el" href="neural_09_09_8hpp.html#839a9222721835f53c5b248241f535f4">neural++.hpp</a>
</ul>
</div>
<hr size="1"><address style="text-align: right;"><small>Generated on Sat Aug 15 02:56:02 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<a href="http://www.doxygen.org/index.html">
<img src="doxygen.png" alt="doxygen" align="middle" border="0"></a> 1.5.6 </small></address>
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@ -12,14 +12,15 @@
<li><a href="namespaces.html"><span>Namespaces</span></a></li>
<li><a href="annotated.html"><span>Classes</span></a></li>
<li><a href="files.html"><span>Files</span></a></li>
<li><a href="examples.html"><span>Examples</span></a></li>
</ul>
</div>
</div>
<div class="contents">
<h1>Neural++ Documentation</h1>
<p>
<h3 align="center">0.3 </h3></div>
<hr size="1"><address style="text-align: right;"><small>Generated on Sat Aug 15 02:56:02 2009 for Neural++ by&nbsp;
<h3 align="center">0.4 </h3></div>
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<a href="http://www.doxygen.org/index.html">
<img src="doxygen.png" alt="doxygen" align="middle" border="0"></a> 1.5.6 </small></address>
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@ -12,6 +12,7 @@
<li class="current"><a href="namespaces.html"><span>Namespaces</span></a></li>
<li><a href="annotated.html"><span>Classes</span></a></li>
<li><a href="files.html"><span>Files</span></a></li>
<li><a href="examples.html"><span>Examples</span></a></li>
</ul>
</div>
<div class="tabs">
@ -31,11 +32,13 @@
Here is a list of all namespace members with links to the namespace documentation for each member:
<p>
<ul>
<li>__actv()
: <a class="el" href="namespaceneuralpp.html#7df3a0de999c7a635f2289749ed4f194">neuralpp</a>
<li>df()
: <a class="el" href="namespaceneuralpp.html#43c8197cc83f65fa9676386579671aec">neuralpp</a>
</ul>
</div>
<hr size="1"><address style="text-align: right;"><small>Generated on Sat Aug 15 02:56:02 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<a href="http://www.doxygen.org/index.html">
<img src="doxygen.png" alt="doxygen" align="middle" border="0"></a> 1.5.6 </small></address>
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@ -12,6 +12,7 @@
<li class="current"><a href="namespaces.html"><span>Namespaces</span></a></li>
<li><a href="annotated.html"><span>Classes</span></a></li>
<li><a href="files.html"><span>Files</span></a></li>
<li><a href="examples.html"><span>Examples</span></a></li>
</ul>
</div>
<div class="tabs">
@ -31,11 +32,13 @@
&nbsp;
<p>
<ul>
<li>__actv()
: <a class="el" href="namespaceneuralpp.html#7df3a0de999c7a635f2289749ed4f194">neuralpp</a>
<li>df()
: <a class="el" href="namespaceneuralpp.html#43c8197cc83f65fa9676386579671aec">neuralpp</a>
</ul>
</div>
<hr size="1"><address style="text-align: right;"><small>Generated on Sat Aug 15 02:56:02 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<a href="http://www.doxygen.org/index.html">
<img src="doxygen.png" alt="doxygen" align="middle" border="0"></a> 1.5.6 </small></address>
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@ -12,6 +12,7 @@
<li class="current"><a href="namespaces.html"><span>Namespaces</span></a></li>
<li><a href="annotated.html"><span>Classes</span></a></li>
<li><a href="files.html"><span>Files</span></a></li>
<li><a href="examples.html"><span>Examples</span></a></li>
</ul>
</div>
<div class="tabs">
@ -46,12 +47,49 @@
<tr><td class="memItemLeft" nowrap align="right" valign="top">struct &nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="structneuralpp_1_1synrecord.html">synrecord</a></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">class &nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1NetworkFileNotFoundException.html">NetworkFileNotFoundException</a></td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Exception thrown when doing an attempt to load a network from an invalid file. <a href="classneuralpp_1_1NetworkFileNotFoundException.html#_details">More...</a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">class &nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1NetworkFileWriteException.html">NetworkFileWriteException</a></td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Exception thrown when trying to write the network's information to a file that cannot be written. <a href="classneuralpp_1_1NetworkFileWriteException.html#_details">More...</a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">class &nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1InvalidXMLException.html">InvalidXMLException</a></td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Exception thrown when trying parsing an invalid XML. <a href="classneuralpp_1_1InvalidXMLException.html#_details">More...</a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">class &nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1NetworkIndexOutOfBoundsException.html">NetworkIndexOutOfBoundsException</a></td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Exception raised when trying to access a neuron whose index is larger than the number of neurons in the network. <a href="classneuralpp_1_1NetworkIndexOutOfBoundsException.html#_details">More...</a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">class &nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1InvalidSynapticalWeightException.html">InvalidSynapticalWeightException</a></td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Exception raised when, while trying the network or directly, the weight of a synapsis is set to a value |w| &gt; 1. <a href="classneuralpp_1_1InvalidSynapticalWeightException.html#_details">More...</a><br></td></tr>
<tr><td colspan="2"><br><h2>Functions</h2></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">double&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespaceneuralpp.html#43c8197cc83f65fa9676386579671aec">df</a> (double(*f)(double), double x)</td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">double&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespaceneuralpp.html#7df3a0de999c7a635f2289749ed4f194">__actv</a> (double prop)</td></tr>
</table>
<hr><a name="_details"></a><h2>Detailed Description</h2>
Main namespace for the library. <hr><h2>Function Documentation</h2>
<a class="anchor" name="7df3a0de999c7a635f2289749ed4f194"></a><!-- doxytag: member="neuralpp::__actv" ref="7df3a0de999c7a635f2289749ed4f194" args="(double prop)" -->
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<td class="memname">double neuralpp::__actv </td>
<td>(</td>
<td class="paramtype">double&nbsp;</td>
<td class="paramname"> <em>prop</em> </td>
<td>&nbsp;)&nbsp;</td>
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<a class="anchor" name="43c8197cc83f65fa9676386579671aec"></a><!-- doxytag: member="neuralpp::df" ref="43c8197cc83f65fa9676386579671aec" args="(double(*f)(double), double x)" -->
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@ -82,7 +120,7 @@ Main namespace for the library. <hr><h2>Function Documentation</h2>
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<hr size="1"><address style="text-align: right;"><small>Generated on Sat Aug 15 02:56:02 2009 for Neural++ by&nbsp;
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@ -26,7 +27,7 @@
<tr><td class="indexkey"><a class="el" href="namespaceneuralpp.html">neuralpp</a></td><td class="indexvalue">Main namespace for the library </td></tr>
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<h1>neural++.hpp</h1><a href="neural_09_09_8hpp.html">Go to the documentation of this file.</a><div class="fragment"><pre class="fragment"><a name="l00001"></a>00001 <span class="comment">/**************************************************************************************************</span>
<a name="l00002"></a>00002 <span class="comment"> * LibNeural++ v.0.2 - All-purpose library for managing neural networks *</span>
<a name="l00002"></a>00002 <span class="comment"> * LibNeural++ v.0.4 - All-purpose library for managing neural networks *</span>
<a name="l00003"></a>00003 <span class="comment"> * Copyright (C) 2009, BlackLight *</span>
<a name="l00004"></a>00004 <span class="comment"> * *</span>
<a name="l00005"></a>00005 <span class="comment"> * This program is free software: you can redistribute it and/or modify it under the terms of the *</span>
@ -27,217 +28,216 @@
<a name="l00011"></a>00011 <span class="comment"> * this program. If not, see &lt;http://www.gnu.org/licenses/&gt;. *</span>
<a name="l00012"></a>00012 <span class="comment"> **************************************************************************************************/</span>
<a name="l00013"></a>00013
<a name="l00014"></a>00014 <span class="comment">//#ifndef __cplusplus</span>
<a name="l00015"></a>00015 <span class="comment">//#error "This is a C++ library, you know, so you'd better use a C++ compiler to compile it"</span>
<a name="l00016"></a>00016 <span class="comment">//#else</span>
<a name="l00017"></a>00017
<a name="l00018"></a>00018 <span class="preprocessor">#ifndef __NEURALPP</span>
<a name="l00019"></a>00019 <span class="preprocessor"></span><span class="preprocessor">#define __NEURALPP</span>
<a name="l00020"></a>00020 <span class="preprocessor"></span>
<a name="l00021"></a>00021 <span class="preprocessor">#include &lt;vector&gt;</span>
<a name="l00022"></a>00022 <span class="preprocessor">#include &lt;string&gt;</span>
<a name="l00023"></a>00023 <span class="preprocessor">#include &lt;cmath&gt;</span>
<a name="l00024"></a>00024
<a name="l00025"></a>00025 <span class="preprocessor">#include "<a class="code" href="neural_09_09__exception_8hpp.html">neural++_exception.hpp</a>"</span>
<a name="l00026"></a>00026 <span class="keyword">using namespace </span>std;
<a name="l00027"></a>00027
<a name="l00029"></a><a class="code" href="neural_09_09_8hpp.html#839a9222721835f53c5b248241f535f4">00029</a> <span class="preprocessor">#define RAND (double) ( (rand() / (RAND_MAX/2)) - 1)</span>
<a name="l00030"></a>00030 <span class="preprocessor"></span>
<a name="l00032"></a><a class="code" href="neural_09_09_8hpp.html#05e2bb5b9fc32f0b6b4d84fe43177d72">00032</a> <span class="preprocessor">#define BETA0 0.8</span>
<a name="l00033"></a>00033 <span class="preprocessor"></span>
<a name="l00038"></a>00038 <span class="keyword">namespace </span>neuralpp {
<a name="l00039"></a>00039 <span class="keyword">class </span>Synapsis;
<a name="l00040"></a>00040 <span class="keyword">class </span>Neuron;
<a name="l00041"></a>00041 <span class="keyword">class </span>Layer;
<a name="l00042"></a>00042 <span class="keyword">class </span>NeuralNet;
<a name="l00043"></a>00043
<a name="l00044"></a>00044 <span class="keywordtype">double</span> <a class="code" href="namespaceneuralpp.html#43c8197cc83f65fa9676386579671aec">df</a> (<span class="keywordtype">double</span> (*f)(<span class="keywordtype">double</span>), <span class="keywordtype">double</span> x);
<a name="l00045"></a>00045
<a name="l00050"></a><a class="code" href="classneuralpp_1_1NeuralNet.html">00050</a> <span class="keyword">class </span><a class="code" href="classneuralpp_1_1NeuralNet.html" title="Main project&amp;#39;s class.">NeuralNet</a> {
<a name="l00051"></a><a class="code" href="classneuralpp_1_1NeuralNet.html#4cb52dae7b43d03fac73afca7b9f3a51">00051</a> <span class="keywordtype">int</span> <a class="code" href="classneuralpp_1_1NeuralNet.html#4cb52dae7b43d03fac73afca7b9f3a51">epochs</a>;
<a name="l00052"></a><a class="code" href="classneuralpp_1_1NeuralNet.html#4f88106c9e542c39eac43b4ca1974a2a">00052</a> <span class="keywordtype">int</span> <a class="code" href="classneuralpp_1_1NeuralNet.html#4f88106c9e542c39eac43b4ca1974a2a">ref_epochs</a>;
<a name="l00053"></a><a class="code" href="classneuralpp_1_1NeuralNet.html#6bd7be443e46b2fdbf1da2edb8e611ab">00053</a> <span class="keywordtype">double</span> <a class="code" href="classneuralpp_1_1NeuralNet.html#6bd7be443e46b2fdbf1da2edb8e611ab">l_rate</a>;
<a name="l00054"></a><a class="code" href="classneuralpp_1_1NeuralNet.html#261f5f68fcc5be54250cfa03945266dd">00054</a> <span class="keywordtype">double</span> <a class="code" href="classneuralpp_1_1NeuralNet.html#261f5f68fcc5be54250cfa03945266dd">ex</a>;
<a name="l00055"></a>00055
<a name="l00060"></a>00060 <span class="keywordtype">void</span> <a class="code" href="classneuralpp_1_1NeuralNet.html#94169c89a7cd47122ab5dbf1d5c5e108" title="It updates the weights of the net&amp;#39;s synapsis through back-propagation.">updateWeights</a>();
<a name="l00061"></a>00061
<a name="l00067"></a>00067 <span class="keywordtype">void</span> <a class="code" href="classneuralpp_1_1NeuralNet.html#62695a82dfb1df758a44150921aec8e0" title="It commits the changes made by updateWeights() to the layer l.">commitChanges</a> (<a class="code" href="classneuralpp_1_1Layer.html" title="Class for managing layers of neurons.">Layer</a> *l);
<a name="l00068"></a>00068
<a name="l00074"></a>00074 <span class="keywordtype">double</span> <a class="code" href="classneuralpp_1_1NeuralNet.html#0616c51404efaca2714e37dd7478997e" title="Get the error made on the expected result as |v-v&amp;#39;|/v.">error</a>(<span class="keywordtype">double</span> <a class="code" href="classneuralpp_1_1NeuralNet.html#261f5f68fcc5be54250cfa03945266dd">ex</a>) <span class="keyword">const</span>;
<a name="l00075"></a>00075
<a name="l00080"></a>00080 double (*<a class="code" href="classneuralpp_1_1NeuralNet.html#c1469e6afd87d85b82f14bc246f82457" title="Private pointer to function, containing the function to be used as activation function...">actv_f</a>)(double);
<a name="l00081"></a>00081
<a name="l00082"></a>00082 <span class="keyword">public</span>:
<a name="l00083"></a><a class="code" href="classneuralpp_1_1NeuralNet.html#e2b4e8405f9d25edab395d61502bdba9">00083</a> <a class="code" href="classneuralpp_1_1Layer.html" title="Class for managing layers of neurons.">Layer</a>* <a class="code" href="classneuralpp_1_1NeuralNet.html#e2b4e8405f9d25edab395d61502bdba9">input</a>;
<a name="l00084"></a><a class="code" href="classneuralpp_1_1NeuralNet.html#bbdaa1b6c0a1a95d2b18cd25fda2a266">00084</a> <a class="code" href="classneuralpp_1_1Layer.html" title="Class for managing layers of neurons.">Layer</a>* <a class="code" href="classneuralpp_1_1NeuralNet.html#bbdaa1b6c0a1a95d2b18cd25fda2a266">hidden</a>;
<a name="l00085"></a><a class="code" href="classneuralpp_1_1NeuralNet.html#fa9b2dbcbb39d0fc70f790ac24069a74">00085</a> <a class="code" href="classneuralpp_1_1Layer.html" title="Class for managing layers of neurons.">Layer</a>* <a class="code" href="classneuralpp_1_1NeuralNet.html#fa9b2dbcbb39d0fc70f790ac24069a74">output</a>;
<a name="l00086"></a>00086
<a name="l00090"></a><a class="code" href="classneuralpp_1_1NeuralNet.html#94c36c94060e785ea67a0014c4182f8f6d06b4fe9414a158c97aee1a3679a904">00090</a> <span class="keyword">typedef</span> <span class="keyword">enum</span> { <a class="code" href="classneuralpp_1_1NeuralNet.html#94c36c94060e785ea67a0014c4182f8f5ec2727c0756ddb097b53efe49b81afb">file</a>, <a class="code" href="classneuralpp_1_1NeuralNet.html#94c36c94060e785ea67a0014c4182f8f6d06b4fe9414a158c97aee1a3679a904">str</a> } <a class="code" href="classneuralpp_1_1NeuralNet.html#94c36c94060e785ea67a0014c4182f8f" title="Enum to choose the eventual training source for our network (XML from a file or from...">source</a>;
<a name="l00091"></a>00091
<a name="l00095"></a><a class="code" href="classneuralpp_1_1NeuralNet.html#92b145f2f6f00bf1ba645ce2235882c2">00095</a> <a class="code" href="classneuralpp_1_1NeuralNet.html#92b145f2f6f00bf1ba645ce2235882c2" title="Empty constructor for the class - it just makes nothing.">NeuralNet</a>() {}
<a name="l00014"></a>00014 <span class="preprocessor">#ifndef __NEURALPP</span>
<a name="l00015"></a>00015 <span class="preprocessor"></span><span class="preprocessor">#define __NEURALPP</span>
<a name="l00016"></a>00016 <span class="preprocessor"></span>
<a name="l00017"></a>00017 <span class="preprocessor">#include &lt;vector&gt;</span>
<a name="l00018"></a>00018 <span class="preprocessor">#include &lt;string&gt;</span>
<a name="l00019"></a>00019 <span class="preprocessor">#include &lt;cmath&gt;</span>
<a name="l00020"></a>00020
<a name="l00021"></a>00021 <span class="preprocessor">#include "<a class="code" href="neural_09_09__exception_8hpp.html">neural++_exception.hpp</a>"</span>
<a name="l00022"></a>00022
<a name="l00024"></a><a class="code" href="neural_09_09_8hpp.html#839a9222721835f53c5b248241f535f4">00024</a> <span class="preprocessor">#define RAND (double) ( (rand() / (RAND_MAX/2)) - 1)</span>
<a name="l00025"></a>00025 <span class="preprocessor"></span>
<a name="l00027"></a><a class="code" href="neural_09_09_8hpp.html#05e2bb5b9fc32f0b6b4d84fe43177d72">00027</a> <span class="preprocessor">#define BETA0 1.0</span>
<a name="l00028"></a>00028 <span class="preprocessor"></span>
<a name="l00033"></a>00033 <span class="keyword">namespace </span>neuralpp {
<a name="l00034"></a>00034 <span class="keyword">class </span>Synapsis;
<a name="l00035"></a>00035 <span class="keyword">class </span>Neuron;
<a name="l00036"></a>00036 <span class="keyword">class </span>Layer;
<a name="l00037"></a>00037 <span class="keyword">class </span>NeuralNet;
<a name="l00038"></a>00038
<a name="l00039"></a>00039 <span class="keywordtype">double</span> <a class="code" href="namespaceneuralpp.html#43c8197cc83f65fa9676386579671aec">df</a> (<span class="keywordtype">double</span> (*f)(<span class="keywordtype">double</span>), <span class="keywordtype">double</span> x);
<a name="l00040"></a>00040 <span class="keywordtype">double</span> <a class="code" href="namespaceneuralpp.html#7df3a0de999c7a635f2289749ed4f194">__actv</a>(<span class="keywordtype">double</span> prop);
<a name="l00041"></a>00041
<a name="l00064"></a><a class="code" href="classneuralpp_1_1NeuralNet.html">00064</a> <span class="keyword">class </span><a class="code" href="classneuralpp_1_1NeuralNet.html" title="Main project&amp;#39;s class.">NeuralNet</a> {
<a name="l00065"></a><a class="code" href="classneuralpp_1_1NeuralNet.html#4cb52dae7b43d03fac73afca7b9f3a51">00065</a> <span class="keywordtype">int</span> <a class="code" href="classneuralpp_1_1NeuralNet.html#4cb52dae7b43d03fac73afca7b9f3a51">epochs</a>;
<a name="l00066"></a><a class="code" href="classneuralpp_1_1NeuralNet.html#4f88106c9e542c39eac43b4ca1974a2a">00066</a> <span class="keywordtype">int</span> <a class="code" href="classneuralpp_1_1NeuralNet.html#4f88106c9e542c39eac43b4ca1974a2a">ref_epochs</a>;
<a name="l00067"></a><a class="code" href="classneuralpp_1_1NeuralNet.html#6bd7be443e46b2fdbf1da2edb8e611ab">00067</a> <span class="keywordtype">double</span> <a class="code" href="classneuralpp_1_1NeuralNet.html#6bd7be443e46b2fdbf1da2edb8e611ab">l_rate</a>;
<a name="l00068"></a><a class="code" href="classneuralpp_1_1NeuralNet.html#327dbfdd72b0a74293f8f29630525aa3">00068</a> <span class="keywordtype">double</span> <a class="code" href="classneuralpp_1_1NeuralNet.html#327dbfdd72b0a74293f8f29630525aa3">threshold</a>;
<a name="l00069"></a><a class="code" href="classneuralpp_1_1NeuralNet.html#a9e4ff43427f56663739c4c7450de8ee">00069</a> std::vector&lt;double&gt; <a class="code" href="classneuralpp_1_1NeuralNet.html#a9e4ff43427f56663739c4c7450de8ee">expect</a>;
<a name="l00070"></a>00070
<a name="l00075"></a>00075 <span class="keywordtype">void</span> <a class="code" href="classneuralpp_1_1NeuralNet.html#94169c89a7cd47122ab5dbf1d5c5e108" title="It updates the weights of the net&amp;#39;s synapsis through back-propagation.">updateWeights</a>();
<a name="l00076"></a>00076
<a name="l00082"></a>00082 <span class="keywordtype">void</span> <a class="code" href="classneuralpp_1_1NeuralNet.html#f697a8d9967ad8f03e5a16a42cd110c5" title="It commits the changes made by updateWeights() to the layer l.">commitChanges</a> (<a class="code" href="classneuralpp_1_1Layer.html" title="Class for managing layers of neurons.">Layer</a>&amp; l);
<a name="l00083"></a>00083
<a name="l00089"></a>00089 <span class="keywordtype">double</span> <a class="code" href="classneuralpp_1_1NeuralNet.html#8a140d28e6dd4097470c7c138801ad01" title="Get the error made on the expected result as squared deviance.">error</a> (<span class="keywordtype">double</span> ex);
<a name="l00090"></a>00090
<a name="l00095"></a>00095 double (*<a class="code" href="classneuralpp_1_1NeuralNet.html#c1469e6afd87d85b82f14bc246f82457" title="Private pointer to function, containing the function to be used as activation function...">actv_f</a>)(double);
<a name="l00096"></a>00096
<a name="l00107"></a>00107 <a class="code" href="classneuralpp_1_1NeuralNet.html#92b145f2f6f00bf1ba645ce2235882c2" title="Empty constructor for the class - it just makes nothing.">NeuralNet</a> (<span class="keywordtype">size_t</span> in_size, <span class="keywordtype">size_t</span> hidden_size, <span class="keywordtype">size_t</span> out_size, <span class="keywordtype">double</span> l, <span class="keywordtype">int</span> e);
<a name="l00108"></a>00108
<a name="l00114"></a>00114 <a class="code" href="classneuralpp_1_1NeuralNet.html#92b145f2f6f00bf1ba645ce2235882c2" title="Empty constructor for the class - it just makes nothing.">NeuralNet</a> (<span class="keyword">const</span> <span class="keywordtype">string</span> <a class="code" href="classneuralpp_1_1NeuralNet.html#94c36c94060e785ea67a0014c4182f8f5ec2727c0756ddb097b53efe49b81afb">file</a>) <span class="keywordflow">throw</span>(NetworkFileNotFoundException);
<a name="l00115"></a>00115
<a name="l00116"></a>00116
<a name="l00128"></a>00128 <a class="code" href="classneuralpp_1_1NeuralNet.html#92b145f2f6f00bf1ba645ce2235882c2" title="Empty constructor for the class - it just makes nothing.">NeuralNet</a> (<span class="keywordtype">size_t</span> in_size, <span class="keywordtype">size_t</span> hidden_size, <span class="keywordtype">size_t</span> out_size,
<a name="l00129"></a>00129 <span class="keywordtype">double</span>(*actv)(<span class="keywordtype">double</span>), <span class="keywordtype">double</span> l, <span class="keywordtype">int</span> e);
<a name="l00130"></a>00130
<a name="l00136"></a>00136 <span class="keywordtype">double</span> <a class="code" href="classneuralpp_1_1NeuralNet.html#961dce8913264bf64c899dce4e25f810" title="It gets the output of the network (note: the layer output should contain an only...">getOutput</a>() <span class="keyword">const</span>;
<a name="l00137"></a>00137
<a name="l00142"></a>00142 vector&lt;double&gt; <a class="code" href="classneuralpp_1_1NeuralNet.html#a6b8bf3800b43b58843c65fc431207ae" title="It gets the output of the network in case the output layer contains more neurons...">getOutputs</a>();
<a name="l00143"></a>00143
<a name="l00149"></a>00149 <span class="keywordtype">double</span> <a class="code" href="classneuralpp_1_1NeuralNet.html#562dfe9fb8d73bf25a23ce608451d3aa" title="It gets the value expected.">expected</a>() <span class="keyword">const</span>;
<a name="l00150"></a>00150
<a name="l00155"></a>00155 <span class="keywordtype">void</span> <a class="code" href="classneuralpp_1_1NeuralNet.html#b6475762b7e9eab086befdc511f7c236" title="It sets the value you expect from your network.">setExpected</a>(<span class="keywordtype">double</span> <a class="code" href="classneuralpp_1_1NeuralNet.html#261f5f68fcc5be54250cfa03945266dd">ex</a>);
<a name="l00156"></a>00156
<a name="l00162"></a>00162 <span class="keywordtype">void</span> <a class="code" href="classneuralpp_1_1NeuralNet.html#b0bd1daadb06980dff1f50d33a7c098e" title="It updates through back-propagation the weights of the synapsis and computes again...">update</a>();
<a name="l00163"></a>00163
<a name="l00168"></a>00168 <span class="keywordtype">void</span> <a class="code" href="classneuralpp_1_1NeuralNet.html#c129c180647362da963758bfd1ba6890" title="It propagates values through the network.">propagate</a>();
<a name="l00169"></a>00169
<a name="l00174"></a>00174 <span class="keywordtype">void</span> <a class="code" href="classneuralpp_1_1NeuralNet.html#0de170e8ab561ad63d0739b4c4b74f68" title="It sets the input for the network.">setInput</a> (vector&lt;double&gt;&amp; v);
<a name="l00175"></a>00175
<a name="l00180"></a>00180 <span class="keywordtype">void</span> <a class="code" href="classneuralpp_1_1NeuralNet.html#46f23f462318a4ffc037a4e806364c3f" title="It links the layers of the network (input, hidden, output).">link</a>();
<a name="l00181"></a>00181
<a name="l00188"></a>00188 <span class="keywordtype">void</span> <a class="code" href="classneuralpp_1_1NeuralNet.html#fdf94c276720c25e565cac834fe8a407" title="Save a trained neural network to a binary file.">save</a>(<span class="keyword">const</span> <span class="keywordtype">char</span>* fname) <span class="keywordflow">throw</span>(NetworkFileWriteException);
<a name="l00189"></a>00189
<a name="l00197"></a>00197 <span class="keywordtype">void</span> <a class="code" href="classneuralpp_1_1NeuralNet.html#ead4bdef0602a5cadbe3beb685e01f5f" title="Train a network using a training set loaded from an XML file.">train</a> (<span class="keywordtype">string</span> xml, <a class="code" href="classneuralpp_1_1NeuralNet.html#94c36c94060e785ea67a0014c4182f8f" title="Enum to choose the eventual training source for our network (XML from a file or from...">source</a> src) <span class="keywordflow">throw</span>(InvalidXMLException);
<a name="l00097"></a>00097 <span class="keyword">public</span>:
<a name="l00098"></a><a class="code" href="classneuralpp_1_1NeuralNet.html#e2b4e8405f9d25edab395d61502bdba9">00098</a> <a class="code" href="classneuralpp_1_1Layer.html" title="Class for managing layers of neurons.">Layer</a>* <a class="code" href="classneuralpp_1_1NeuralNet.html#e2b4e8405f9d25edab395d61502bdba9">input</a>;
<a name="l00099"></a><a class="code" href="classneuralpp_1_1NeuralNet.html#bbdaa1b6c0a1a95d2b18cd25fda2a266">00099</a> <a class="code" href="classneuralpp_1_1Layer.html" title="Class for managing layers of neurons.">Layer</a>* <a class="code" href="classneuralpp_1_1NeuralNet.html#bbdaa1b6c0a1a95d2b18cd25fda2a266">hidden</a>;
<a name="l00100"></a><a class="code" href="classneuralpp_1_1NeuralNet.html#fa9b2dbcbb39d0fc70f790ac24069a74">00100</a> <a class="code" href="classneuralpp_1_1Layer.html" title="Class for managing layers of neurons.">Layer</a>* <a class="code" href="classneuralpp_1_1NeuralNet.html#fa9b2dbcbb39d0fc70f790ac24069a74">output</a>;
<a name="l00101"></a>00101
<a name="l00105"></a><a class="code" href="classneuralpp_1_1NeuralNet.html#94c36c94060e785ea67a0014c4182f8f6d06b4fe9414a158c97aee1a3679a904">00105</a> <span class="keyword">typedef</span> <span class="keyword">enum</span> { <a class="code" href="classneuralpp_1_1NeuralNet.html#94c36c94060e785ea67a0014c4182f8f5ec2727c0756ddb097b53efe49b81afb">file</a>, <a class="code" href="classneuralpp_1_1NeuralNet.html#94c36c94060e785ea67a0014c4182f8f6d06b4fe9414a158c97aee1a3679a904">str</a> } <a class="code" href="classneuralpp_1_1NeuralNet.html#94c36c94060e785ea67a0014c4182f8f" title="Enum to choose the eventual training source for our network (XML from a file or from...">source</a>;
<a name="l00106"></a>00106
<a name="l00110"></a><a class="code" href="classneuralpp_1_1NeuralNet.html#92b145f2f6f00bf1ba645ce2235882c2">00110</a> <a class="code" href="classneuralpp_1_1NeuralNet.html#92b145f2f6f00bf1ba645ce2235882c2" title="Empty constructor for the class - it just makes nothing.">NeuralNet</a>() {}
<a name="l00111"></a>00111
<a name="l00125"></a>00125 <a class="code" href="classneuralpp_1_1NeuralNet.html#92b145f2f6f00bf1ba645ce2235882c2" title="Empty constructor for the class - it just makes nothing.">NeuralNet</a> (<span class="keywordtype">size_t</span> in_size, <span class="keywordtype">size_t</span> hidden_size, <span class="keywordtype">size_t</span> out_size, <span class="keywordtype">double</span> l,
<a name="l00126"></a>00126 <span class="keywordtype">int</span> e, <span class="keywordtype">double</span> th = 0.0, <span class="keywordtype">double</span> (*a)(<span class="keywordtype">double</span>) = __actv);
<a name="l00127"></a>00127
<a name="l00133"></a>00133 <a class="code" href="classneuralpp_1_1NeuralNet.html#92b145f2f6f00bf1ba645ce2235882c2" title="Empty constructor for the class - it just makes nothing.">NeuralNet</a> (<span class="keyword">const</span> std::string <a class="code" href="classneuralpp_1_1NeuralNet.html#94c36c94060e785ea67a0014c4182f8f5ec2727c0756ddb097b53efe49b81afb">file</a>) <span class="keywordflow">throw</span>(<a class="code" href="classneuralpp_1_1NetworkFileNotFoundException.html" title="Exception thrown when doing an attempt to load a network from an invalid file.">NetworkFileNotFoundException</a>);
<a name="l00134"></a>00134
<a name="l00140"></a>00140 <span class="keywordtype">double</span> <a class="code" href="classneuralpp_1_1NeuralNet.html#961dce8913264bf64c899dce4e25f810" title="It gets the output of the network (note: the layer output should contain an only...">getOutput</a>() <span class="keyword">const</span>;
<a name="l00141"></a>00141
<a name="l00146"></a>00146 <span class="keywordtype">double</span> <a class="code" href="classneuralpp_1_1NeuralNet.html#e08cdcf4b70f987700e553d9914f6179" title="Get the threshold of the neurons in the network.">getThreshold</a>() <span class="keyword">const</span>;
<a name="l00147"></a>00147
<a name="l00152"></a>00152 std::vector&lt;double&gt; <a class="code" href="classneuralpp_1_1NeuralNet.html#e6d2215ecc8b560db2f6797db642191c" title="It gets the output of the network in case the output layer contains more neurons...">getOutputs</a>();
<a name="l00153"></a>00153
<a name="l00159"></a>00159 <span class="keywordtype">double</span> <a class="code" href="classneuralpp_1_1NeuralNet.html#562dfe9fb8d73bf25a23ce608451d3aa" title="Get the expected value (in case you have an only neuron in output layer).">expected</a>() <span class="keyword">const</span>;
<a name="l00160"></a>00160
<a name="l00166"></a>00166 std::vector&lt;double&gt; <a class="code" href="classneuralpp_1_1NeuralNet.html#51a1851ed07b85bec091c9053ae99cf7" title="Get the expected value (in case you have an only neuron in output layer).">getExpected</a>() <span class="keyword">const</span>;
<a name="l00167"></a>00167
<a name="l00172"></a>00172 <span class="keywordtype">void</span> <a class="code" href="classneuralpp_1_1NeuralNet.html#b6475762b7e9eab086befdc511f7c236" title="It sets the value you expect from your network (in case the network has an only neuron...">setExpected</a>(<span class="keywordtype">double</span> ex);
<a name="l00173"></a>00173
<a name="l00178"></a>00178 <span class="keywordtype">void</span> <a class="code" href="classneuralpp_1_1NeuralNet.html#b6475762b7e9eab086befdc511f7c236" title="It sets the value you expect from your network (in case the network has an only neuron...">setExpected</a>(std::vector&lt;double&gt; ex);
<a name="l00179"></a>00179
<a name="l00185"></a>00185 <span class="keywordtype">void</span> <a class="code" href="classneuralpp_1_1NeuralNet.html#b0bd1daadb06980dff1f50d33a7c098e" title="It updates through back-propagation the weights of the synapsis and computes again...">update</a>();
<a name="l00186"></a>00186
<a name="l00191"></a>00191 <span class="keywordtype">void</span> <a class="code" href="classneuralpp_1_1NeuralNet.html#c129c180647362da963758bfd1ba6890" title="It propagates values through the network.">propagate</a>();
<a name="l00192"></a>00192
<a name="l00197"></a>00197 <span class="keywordtype">void</span> <a class="code" href="classneuralpp_1_1NeuralNet.html#405b32d2928344314ecf0469070b0f17" title="It sets the input for the network.">setInput</a> (std::vector&lt;double&gt; v);
<a name="l00198"></a>00198
<a name="l00203"></a>00203 <span class="keyword">static</span> <span class="keywordtype">void</span> <a class="code" href="classneuralpp_1_1NeuralNet.html#45c7645d4affe65752d37cd230afba24" title="Initialize the training XML for the neural network.">initXML</a> (<span class="keywordtype">string</span>&amp; xml);
<a name="l00203"></a>00203 <span class="keywordtype">void</span> <a class="code" href="classneuralpp_1_1NeuralNet.html#46f23f462318a4ffc037a4e806364c3f" title="It links the layers of the network (input, hidden, output).">link</a>();
<a name="l00204"></a>00204
<a name="l00211"></a>00211 <span class="keyword">static</span> vector&lt;double&gt; <a class="code" href="classneuralpp_1_1NeuralNet.html#e07af23ceb8666518da0c035bf1e0376" title="Splits a string into a vector of doubles, given a delimitator.">split</a> (<span class="keywordtype">char</span> delim, <span class="keywordtype">string</span> <a class="code" href="classneuralpp_1_1NeuralNet.html#94c36c94060e785ea67a0014c4182f8f6d06b4fe9414a158c97aee1a3679a904">str</a>);
<a name="l00211"></a>00211 <span class="keywordtype">void</span> <a class="code" href="classneuralpp_1_1NeuralNet.html#fdf94c276720c25e565cac834fe8a407" title="Save a trained neural network to a binary file.">save</a> (<span class="keyword">const</span> <span class="keywordtype">char</span>* fname) <span class="keywordflow">throw</span>(<a class="code" href="classneuralpp_1_1NetworkFileWriteException.html" title="Exception thrown when trying to write the network&amp;#39;s information to a file that...">NetworkFileWriteException</a>);
<a name="l00212"></a>00212
<a name="l00225"></a>00225 <span class="keyword">static</span> <span class="keywordtype">string</span> <a class="code" href="classneuralpp_1_1NeuralNet.html#4be31ecb0b543a192997bd83c6995ccb" title="Get a training set from a string and copies it to an XML For example, these strings...">XMLFromSet</a> (<span class="keywordtype">int</span> <span class="keywordtype">id</span>, <span class="keywordtype">string</span> <span class="keyword">set</span>);
<a name="l00226"></a>00226
<a name="l00231"></a>00231 <span class="keyword">static</span> <span class="keywordtype">void</span> <a class="code" href="classneuralpp_1_1NeuralNet.html#28b9966c5f197b8e86d57dd104aa32a6" title="Closes an open XML document generated by &amp;quot;initXML&amp;quot; and &amp;quot;XMLFromSet&amp;quot;...">closeXML</a>(<span class="keywordtype">string</span>&amp; xml);
<a name="l00232"></a>00232 };
<a name="l00233"></a>00233
<a name="l00239"></a><a class="code" href="classneuralpp_1_1Synapsis.html">00239</a> <span class="keyword">class </span><a class="code" href="classneuralpp_1_1Synapsis.html" title="Class for managing synapsis.">Synapsis</a> {
<a name="l00240"></a><a class="code" href="classneuralpp_1_1Synapsis.html#617fdc4305f8f1850eac267a7ee22660">00240</a> <span class="keywordtype">double</span> <a class="code" href="classneuralpp_1_1Synapsis.html#617fdc4305f8f1850eac267a7ee22660">delta</a>;
<a name="l00241"></a><a class="code" href="classneuralpp_1_1Synapsis.html#65471cd6c9ef87609dfa4b0e5fafa708">00241</a> <span class="keywordtype">double</span> <a class="code" href="classneuralpp_1_1Synapsis.html#65471cd6c9ef87609dfa4b0e5fafa708">prev_delta</a>;
<a name="l00242"></a><a class="code" href="classneuralpp_1_1Synapsis.html#0bc523a8135ebbb5c0da932939d30ed7">00242</a> <span class="keywordtype">double</span> <a class="code" href="classneuralpp_1_1Synapsis.html#0bc523a8135ebbb5c0da932939d30ed7">weight</a>;
<a name="l00243"></a>00243
<a name="l00244"></a><a class="code" href="classneuralpp_1_1Synapsis.html#83d41c158054b08bd05051736e89a0ad">00244</a> <a class="code" href="classneuralpp_1_1Neuron.html" title="Class for managing neurons.">Neuron</a> *<a class="code" href="classneuralpp_1_1Synapsis.html#83d41c158054b08bd05051736e89a0ad">in</a>;
<a name="l00245"></a><a class="code" href="classneuralpp_1_1Synapsis.html#fb219e05038fa0da20db1082ab0500be">00245</a> <a class="code" href="classneuralpp_1_1Neuron.html" title="Class for managing neurons.">Neuron</a> *<a class="code" href="classneuralpp_1_1Synapsis.html#fb219e05038fa0da20db1082ab0500be">out</a>;
<a name="l00246"></a>00246
<a name="l00247"></a>00247 double (*<a class="code" href="classneuralpp_1_1Synapsis.html#2539b9eef2ff0f3522aea8d89e394f02">actv_f</a>)(double);
<a name="l00248"></a>00248
<a name="l00249"></a>00249 <span class="keyword">public</span>:
<a name="l00257"></a>00257 <a class="code" href="classneuralpp_1_1Synapsis.html#0729de9e737b9967421edcfc4b410bd8" title="Constructor.">Synapsis</a>(<a class="code" href="classneuralpp_1_1Neuron.html" title="Class for managing neurons.">Neuron</a>* i, <a class="code" href="classneuralpp_1_1Neuron.html" title="Class for managing neurons.">Neuron</a>* o, <span class="keywordtype">double</span> w, <span class="keywordtype">double</span> d);
<a name="l00258"></a>00258
<a name="l00265"></a>00265 <a class="code" href="classneuralpp_1_1Synapsis.html#0729de9e737b9967421edcfc4b410bd8" title="Constructor.">Synapsis</a> (<a class="code" href="classneuralpp_1_1Neuron.html" title="Class for managing neurons.">Neuron</a>* i, <a class="code" href="classneuralpp_1_1Neuron.html" title="Class for managing neurons.">Neuron</a>* o, <span class="keywordtype">double</span>(*a)(<span class="keywordtype">double</span>));
<a name="l00266"></a>00266
<a name="l00274"></a>00274 <a class="code" href="classneuralpp_1_1Synapsis.html#0729de9e737b9967421edcfc4b410bd8" title="Constructor.">Synapsis</a> (<a class="code" href="classneuralpp_1_1Neuron.html" title="Class for managing neurons.">Neuron</a>* i, <a class="code" href="classneuralpp_1_1Neuron.html" title="Class for managing neurons.">Neuron</a>* o,
<a name="l00275"></a>00275 <span class="keywordtype">double</span> w, <span class="keywordtype">double</span>(*a)(<span class="keywordtype">double</span>));
<a name="l00276"></a>00276
<a name="l00280"></a>00280 <a class="code" href="classneuralpp_1_1Neuron.html" title="Class for managing neurons.">Neuron</a>* <a class="code" href="classneuralpp_1_1Synapsis.html#5ba8a93a5741f4855390eb8a46e99435">getIn</a>();
<a name="l00281"></a>00281
<a name="l00285"></a>00285 <a class="code" href="classneuralpp_1_1Neuron.html" title="Class for managing neurons.">Neuron</a>* <a class="code" href="classneuralpp_1_1Synapsis.html#61c9a04e03291a01f44520cef143cbdd">getOut</a>();
<a name="l00286"></a>00286
<a name="l00291"></a>00291 <span class="keywordtype">void</span> <a class="code" href="classneuralpp_1_1Synapsis.html#acee77d0fdf9889464ab5ed27beae0ff" title="Set the weight of the synapsis.">setWeight</a>(<span class="keywordtype">double</span> w) <span class="keywordflow">throw</span>(InvalidSynapticalWeightException);
<a name="l00292"></a>00292
<a name="l00298"></a>00298 <span class="keywordtype">void</span> <a class="code" href="classneuralpp_1_1Synapsis.html#429ad5b25930faf436a9d725582802e1" title="It sets the delta (how much to change the weight after an update) of the synapsis...">setDelta</a>(<span class="keywordtype">double</span> d) <span class="keywordflow">throw</span>(InvalidSynapticalWeightException);
<a name="l00299"></a>00299
<a name="l00304"></a>00304 <span class="keywordtype">double</span> <a class="code" href="classneuralpp_1_1Synapsis.html#aa79c16ec6b59949e5d2f75a3f10d530" title="Return the weight of the synapsis.">getWeight</a>();
<a name="l00305"></a>00305
<a name="l00310"></a>00310 <span class="keywordtype">double</span> <a class="code" href="classneuralpp_1_1Synapsis.html#18f15b920609be8b818d43a0227aada5" title="Return the delta of the synapsis.">getDelta</a>();
<a name="l00311"></a>00311
<a name="l00316"></a>00316 <span class="keywordtype">double</span> <a class="code" href="classneuralpp_1_1Synapsis.html#2fe3e9ec97542f1476d8b9306aa09756" title="Get the delta of the synapsis at the previous iteration.">getPrevDelta</a>();
<a name="l00317"></a>00317
<a name="l00328"></a>00328 <span class="keywordtype">double</span> <a class="code" href="classneuralpp_1_1Synapsis.html#ecdb17182de791f7fdd417232e184350" title="Get the inertial momentum of a synapsis.">momentum</a> (<span class="keywordtype">int</span> N, <span class="keywordtype">int</span> x);
<a name="l00329"></a>00329 };
<a name="l00330"></a>00330
<a name="l00336"></a><a class="code" href="classneuralpp_1_1Neuron.html">00336</a> <span class="keyword">class </span><a class="code" href="classneuralpp_1_1Neuron.html" title="Class for managing neurons.">Neuron</a> {
<a name="l00337"></a><a class="code" href="classneuralpp_1_1Neuron.html#eec680c47272b2465e8d8a998c359853">00337</a> <span class="keywordtype">double</span> <a class="code" href="classneuralpp_1_1Neuron.html#eec680c47272b2465e8d8a998c359853">actv_val</a>;
<a name="l00338"></a><a class="code" href="classneuralpp_1_1Neuron.html#da75259de98b1a893c736666af6bfdc3">00338</a> <span class="keywordtype">double</span> <a class="code" href="classneuralpp_1_1Neuron.html#da75259de98b1a893c736666af6bfdc3">prop_val</a>;
<a name="l00339"></a>00339
<a name="l00340"></a><a class="code" href="classneuralpp_1_1Neuron.html#ead827210fa18c2baae03927b2c798ff">00340</a> vector&lt; Synapsis &gt; <a class="code" href="classneuralpp_1_1Neuron.html#ead827210fa18c2baae03927b2c798ff">in</a>;
<a name="l00341"></a><a class="code" href="classneuralpp_1_1Neuron.html#82a4297f84d6403e52a8386d26117b4f">00341</a> vector&lt; Synapsis &gt; <a class="code" href="classneuralpp_1_1Neuron.html#82a4297f84d6403e52a8386d26117b4f">out</a>;
<a name="l00342"></a>00342
<a name="l00343"></a>00343 double (*<a class="code" href="classneuralpp_1_1Neuron.html#198ddd0d11a26d0052d52b787d6a0df0">actv_f</a>)(double);
<a name="l00344"></a>00344
<a name="l00345"></a>00345 <span class="keyword">public</span>:
<a name="l00350"></a>00350 <a class="code" href="classneuralpp_1_1Neuron.html#9863a08b73bc97c8b514aca6c580ff7b" title="Constructor.">Neuron</a> (<span class="keywordtype">double</span> (*a)(<span class="keywordtype">double</span>));
<a name="l00351"></a>00351
<a name="l00358"></a>00358 <a class="code" href="classneuralpp_1_1Neuron.html#9863a08b73bc97c8b514aca6c580ff7b" title="Constructor.">Neuron</a> (vector&lt;Synapsis&gt; <a class="code" href="classneuralpp_1_1Neuron.html#ead827210fa18c2baae03927b2c798ff">in</a>, vector&lt;Synapsis&gt; <a class="code" href="classneuralpp_1_1Neuron.html#82a4297f84d6403e52a8386d26117b4f">out</a>,
<a name="l00359"></a>00359 <span class="keywordtype">double</span> (*a)(<span class="keywordtype">double</span>));
<a name="l00360"></a>00360
<a name="l00366"></a>00366 <a class="code" href="classneuralpp_1_1Synapsis.html" title="Class for managing synapsis.">Synapsis</a>&amp; <a class="code" href="classneuralpp_1_1Neuron.html#29f2d9dcc4ca34f224d4dc39bb2f180a" title="Get the i-th synapsis connected on the input of the neuron.">synIn</a> (<span class="keywordtype">size_t</span> i);
<a name="l00367"></a>00367
<a name="l00373"></a>00373 <a class="code" href="classneuralpp_1_1Synapsis.html" title="Class for managing synapsis.">Synapsis</a>&amp; <a class="code" href="classneuralpp_1_1Neuron.html#655f1637e1b754461413ac7fc2ffeebe" title="Get the i-th synapsis connected on the output of the neuron.">synOut</a> (<span class="keywordtype">size_t</span> i);
<a name="l00374"></a>00374
<a name="l00379"></a>00379 <span class="keywordtype">void</span> <a class="code" href="classneuralpp_1_1Neuron.html#583ada6e1dd3f2e113415b4d89196e62" title="It pushes a new input synapsis.">push_in</a> (<a class="code" href="classneuralpp_1_1Synapsis.html" title="Class for managing synapsis.">Synapsis</a>&amp; s);
<a name="l00380"></a>00380
<a name="l00385"></a>00385 <span class="keywordtype">void</span> <a class="code" href="classneuralpp_1_1Neuron.html#bca65db84f56f9d40694bfbcd25812cb" title="It pushes a new output synapsis.">push_out</a> (<a class="code" href="classneuralpp_1_1Synapsis.html" title="Class for managing synapsis.">Synapsis</a>&amp; s);
<a name="l00386"></a>00386
<a name="l00391"></a>00391 <span class="keywordtype">void</span> <a class="code" href="classneuralpp_1_1Neuron.html#ddf00ffef030b27ed11901aad08822bd" title="Change the activation value of the neuron.">setActv</a> (<span class="keywordtype">double</span> a);
<a name="l00392"></a>00392
<a name="l00397"></a>00397 <span class="keywordtype">void</span> <a class="code" href="classneuralpp_1_1Neuron.html#aa6e58f073a76b3481fea9115a4e6ea6" title="Change the propagation value of the neuron.">setProp</a> (<span class="keywordtype">double</span> p);
<a name="l00398"></a>00398
<a name="l00403"></a>00403 <span class="keywordtype">double</span> <a class="code" href="classneuralpp_1_1Neuron.html#55993867179f0ac7d1e0e2c460ceb611" title="Get the activation value of the neuron.">getActv</a>();
<a name="l00404"></a>00404
<a name="l00409"></a>00409 <span class="keywordtype">double</span> <a class="code" href="classneuralpp_1_1Neuron.html#57c022f82213f662e2a263fc134a3fc9" title="Get the propagation value of the neuron.">getProp</a>();
<a name="l00410"></a>00410
<a name="l00414"></a>00414 <span class="keywordtype">double</span> <a class="code" href="classneuralpp_1_1Neuron.html#8b0ca61cd0e047c8691ab39aae56dbda" title="It propagates its activation value to the connected neurons.">propagate</a>();
<a name="l00415"></a>00415
<a name="l00420"></a>00420 <span class="keywordtype">size_t</span> <a class="code" href="classneuralpp_1_1Neuron.html#ad97f1a082d5f969eb4c69ab454ecfbb" title="Get the number of input synapsis for the neuron.">nIn</a>();
<a name="l00421"></a>00421
<a name="l00426"></a>00426 <span class="keywordtype">size_t</span> <a class="code" href="classneuralpp_1_1Neuron.html#fe458021e3b20d58dc608fb94ae2135b" title="Get the number of output synapsis for the neuron.">nOut</a>();
<a name="l00427"></a>00427
<a name="l00431"></a>00431 <span class="keywordtype">void</span> <a class="code" href="classneuralpp_1_1Neuron.html#2e2ccb69277fc3d992a3a3f2360ed154" title="Remove input and output synapsis from a neuron.">synClear</a>();
<a name="l00432"></a>00432 };
<a name="l00433"></a>00433
<a name="l00439"></a><a class="code" href="classneuralpp_1_1Layer.html">00439</a> <span class="keyword">class </span><a class="code" href="classneuralpp_1_1Layer.html" title="Class for managing layers of neurons.">Layer</a> {
<a name="l00440"></a><a class="code" href="classneuralpp_1_1Layer.html#855685c9da56b06b629e13a2f8c719ce">00440</a> vector&lt;Neuron&gt; <a class="code" href="classneuralpp_1_1Layer.html#855685c9da56b06b629e13a2f8c719ce">elements</a>;
<a name="l00441"></a>00441
<a name="l00442"></a>00442 void (*<a class="code" href="classneuralpp_1_1Layer.html#c023a15a16353d0b4f44060a159f550f">update_weights</a>)();
<a name="l00443"></a>00443 double (*<a class="code" href="classneuralpp_1_1Layer.html#824367da29f92253a027a7c5b4a4405e">actv_f</a>)(double);
<a name="l00444"></a>00444
<a name="l00445"></a>00445 <span class="keyword">public</span>:
<a name="l00451"></a>00451 <a class="code" href="classneuralpp_1_1Layer.html#fb08bddd85d36570dabfe915461f07c5" title="Constructor.">Layer</a> (<span class="keywordtype">size_t</span> sz, <span class="keywordtype">double</span> (*a)(<span class="keywordtype">double</span>));
<a name="l00452"></a>00452
<a name="l00459"></a>00459 <a class="code" href="classneuralpp_1_1Layer.html#fb08bddd85d36570dabfe915461f07c5" title="Constructor.">Layer</a> (vector&lt;Neuron&gt;&amp; neurons, <span class="keywordtype">double</span>(*a)(<span class="keywordtype">double</span>));
<a name="l00460"></a>00460
<a name="l00466"></a>00466 <a class="code" href="classneuralpp_1_1Neuron.html" title="Class for managing neurons.">Neuron</a>&amp; <a class="code" href="classneuralpp_1_1Layer.html#45ff7554830558155c6fbce3b6827122" title="Redefinition for operator [].">operator[] </a>(<span class="keywordtype">size_t</span> i) <span class="keywordflow">throw</span>(NetworkIndexOutOfBoundsException);
<a name="l00467"></a>00467
<a name="l00472"></a>00472 <span class="keywordtype">void</span> <a class="code" href="classneuralpp_1_1Layer.html#ac33444fde14633fa1ad4acb024ad150" title="It links a layer to another.">link</a> (<a class="code" href="classneuralpp_1_1Layer.html" title="Class for managing layers of neurons.">Layer</a>&amp; l);
<a name="l00220"></a>00220 <span class="keywordtype">void</span> <a class="code" href="classneuralpp_1_1NeuralNet.html#1c9e17437d41a7048611e21a3cc1c7dd" title="Train a network using a training set loaded from an XML file.">train</a> (std::string xml, <a class="code" href="classneuralpp_1_1NeuralNet.html#94c36c94060e785ea67a0014c4182f8f" title="Enum to choose the eventual training source for our network (XML from a file or from...">source</a> src) <span class="keywordflow">throw</span>(<a class="code" href="classneuralpp_1_1InvalidXMLException.html" title="Exception thrown when trying parsing an invalid XML.">InvalidXMLException</a>);
<a name="l00221"></a>00221
<a name="l00226"></a>00226 <span class="keyword">static</span> <span class="keywordtype">void</span> <a class="code" href="classneuralpp_1_1NeuralNet.html#96da6712a72051cf34ad961761ef6e08" title="Initialize the training XML for the neural network.">initXML</a> (std::string&amp; xml);
<a name="l00227"></a>00227
<a name="l00234"></a>00234 <span class="keyword">static</span> std::vector&lt;double&gt; <a class="code" href="classneuralpp_1_1NeuralNet.html#83c6555520856d5867752904349ab6ca" title="Splits a string into a vector of doubles, given a delimitator.">split</a> (<span class="keywordtype">char</span> delim, std::string <a class="code" href="classneuralpp_1_1NeuralNet.html#94c36c94060e785ea67a0014c4182f8f6d06b4fe9414a158c97aee1a3679a904">str</a>);
<a name="l00235"></a>00235
<a name="l00248"></a>00248 <span class="keyword">static</span> std::string <a class="code" href="classneuralpp_1_1NeuralNet.html#0a2733037af912b3e6a10146e7b7172f" title="Get a training set from a string and copies it to an XML For example, these strings...">XMLFromSet</a> (<span class="keywordtype">int</span>&amp; <span class="keywordtype">id</span>, std::string <span class="keyword">set</span>);
<a name="l00249"></a>00249
<a name="l00254"></a>00254 <span class="keyword">static</span> <span class="keywordtype">void</span> <a class="code" href="classneuralpp_1_1NeuralNet.html#e17732ed578bc4bd6032bfae58a5cf51" title="Closes an open XML document generated by &amp;quot;initXML&amp;quot; and &amp;quot;XMLFromSet&amp;quot;...">closeXML</a>(std::string&amp; xml);
<a name="l00255"></a>00255 };
<a name="l00256"></a>00256
<a name="l00262"></a><a class="code" href="classneuralpp_1_1Synapsis.html">00262</a> <span class="keyword">class </span><a class="code" href="classneuralpp_1_1Synapsis.html" title="Class for managing synapsis.">Synapsis</a> {
<a name="l00263"></a><a class="code" href="classneuralpp_1_1Synapsis.html#617fdc4305f8f1850eac267a7ee22660">00263</a> <span class="keywordtype">double</span> <a class="code" href="classneuralpp_1_1Synapsis.html#617fdc4305f8f1850eac267a7ee22660">delta</a>;
<a name="l00264"></a><a class="code" href="classneuralpp_1_1Synapsis.html#65471cd6c9ef87609dfa4b0e5fafa708">00264</a> <span class="keywordtype">double</span> <a class="code" href="classneuralpp_1_1Synapsis.html#65471cd6c9ef87609dfa4b0e5fafa708">prev_delta</a>;
<a name="l00265"></a><a class="code" href="classneuralpp_1_1Synapsis.html#0bc523a8135ebbb5c0da932939d30ed7">00265</a> <span class="keywordtype">double</span> <a class="code" href="classneuralpp_1_1Synapsis.html#0bc523a8135ebbb5c0da932939d30ed7">weight</a>;
<a name="l00266"></a>00266
<a name="l00267"></a><a class="code" href="classneuralpp_1_1Synapsis.html#83d41c158054b08bd05051736e89a0ad">00267</a> <a class="code" href="classneuralpp_1_1Neuron.html" title="Class for managing neurons.">Neuron</a> *<a class="code" href="classneuralpp_1_1Synapsis.html#83d41c158054b08bd05051736e89a0ad">in</a>;
<a name="l00268"></a><a class="code" href="classneuralpp_1_1Synapsis.html#fb219e05038fa0da20db1082ab0500be">00268</a> <a class="code" href="classneuralpp_1_1Neuron.html" title="Class for managing neurons.">Neuron</a> *<a class="code" href="classneuralpp_1_1Synapsis.html#fb219e05038fa0da20db1082ab0500be">out</a>;
<a name="l00269"></a>00269
<a name="l00270"></a>00270 double (*<a class="code" href="classneuralpp_1_1Synapsis.html#2539b9eef2ff0f3522aea8d89e394f02">actv_f</a>)(double);
<a name="l00271"></a>00271
<a name="l00272"></a>00272 <span class="keyword">public</span>:
<a name="l00280"></a>00280 <a class="code" href="classneuralpp_1_1Synapsis.html#0729de9e737b9967421edcfc4b410bd8" title="Constructor.">Synapsis</a>(<a class="code" href="classneuralpp_1_1Neuron.html" title="Class for managing neurons.">Neuron</a>* i, <a class="code" href="classneuralpp_1_1Neuron.html" title="Class for managing neurons.">Neuron</a>* o, <span class="keywordtype">double</span> w, <span class="keywordtype">double</span> d);
<a name="l00281"></a>00281
<a name="l00288"></a>00288 <a class="code" href="classneuralpp_1_1Synapsis.html#0729de9e737b9967421edcfc4b410bd8" title="Constructor.">Synapsis</a> (<a class="code" href="classneuralpp_1_1Neuron.html" title="Class for managing neurons.">Neuron</a>* i, <a class="code" href="classneuralpp_1_1Neuron.html" title="Class for managing neurons.">Neuron</a>* o, <span class="keywordtype">double</span>(*a)(<span class="keywordtype">double</span>));
<a name="l00289"></a>00289
<a name="l00297"></a>00297 <a class="code" href="classneuralpp_1_1Synapsis.html#0729de9e737b9967421edcfc4b410bd8" title="Constructor.">Synapsis</a> (<a class="code" href="classneuralpp_1_1Neuron.html" title="Class for managing neurons.">Neuron</a>* i, <a class="code" href="classneuralpp_1_1Neuron.html" title="Class for managing neurons.">Neuron</a>* o,
<a name="l00298"></a>00298 <span class="keywordtype">double</span> w, <span class="keywordtype">double</span>(*a)(<span class="keywordtype">double</span>));
<a name="l00299"></a>00299
<a name="l00303"></a>00303 <a class="code" href="classneuralpp_1_1Neuron.html" title="Class for managing neurons.">Neuron</a>* <a class="code" href="classneuralpp_1_1Synapsis.html#298fd3c7483ad572899fecec01ac8fdf">getIn</a>() <span class="keyword">const</span>;
<a name="l00304"></a>00304
<a name="l00308"></a>00308 <a class="code" href="classneuralpp_1_1Neuron.html" title="Class for managing neurons.">Neuron</a>* <a class="code" href="classneuralpp_1_1Synapsis.html#b46d876761a73a24db87f5a144a0e899">getOut</a>() <span class="keyword">const</span>;
<a name="l00309"></a>00309
<a name="l00314"></a>00314 <span class="keywordtype">void</span> <a class="code" href="classneuralpp_1_1Synapsis.html#acee77d0fdf9889464ab5ed27beae0ff" title="Set the weight of the synapsis.">setWeight</a>(<span class="keywordtype">double</span> w) <span class="keywordflow">throw</span>(<a class="code" href="classneuralpp_1_1InvalidSynapticalWeightException.html" title="Exception raised when, while trying the network or directly, the weight of a synapsis...">InvalidSynapticalWeightException</a>);
<a name="l00315"></a>00315
<a name="l00321"></a>00321 <span class="keywordtype">void</span> <a class="code" href="classneuralpp_1_1Synapsis.html#429ad5b25930faf436a9d725582802e1" title="It sets the delta (how much to change the weight after an update) of the synapsis...">setDelta</a>(<span class="keywordtype">double</span> d) <span class="keywordflow">throw</span>(<a class="code" href="classneuralpp_1_1InvalidSynapticalWeightException.html" title="Exception raised when, while trying the network or directly, the weight of a synapsis...">InvalidSynapticalWeightException</a>);
<a name="l00322"></a>00322
<a name="l00327"></a>00327 <span class="keywordtype">double</span> <a class="code" href="classneuralpp_1_1Synapsis.html#bcbf7228632ff4d6bbb67703323d2db0" title="Return the weight of the synapsis.">getWeight</a>() <span class="keyword">const</span>;
<a name="l00328"></a>00328
<a name="l00333"></a>00333 <span class="keywordtype">double</span> <a class="code" href="classneuralpp_1_1Synapsis.html#00c8e9c0804662f2b3247d6dddb4ca6c" title="Return the delta of the synapsis.">getDelta</a>() <span class="keyword">const</span>;
<a name="l00334"></a>00334
<a name="l00339"></a>00339 <span class="keywordtype">double</span> <a class="code" href="classneuralpp_1_1Synapsis.html#0148b9c8db870c928711168702ae51c5" title="Get the delta of the synapsis at the previous iteration.">getPrevDelta</a>() <span class="keyword">const</span>;
<a name="l00340"></a>00340
<a name="l00351"></a>00351 <span class="keywordtype">double</span> <a class="code" href="classneuralpp_1_1Synapsis.html#cff10a022d4c021688e4df944c05d8bd" title="Get the inertial momentum of a synapsis.">momentum</a> (<span class="keywordtype">int</span> N, <span class="keywordtype">int</span> x) <span class="keyword">const</span>;
<a name="l00352"></a>00352 };
<a name="l00353"></a>00353
<a name="l00359"></a><a class="code" href="classneuralpp_1_1Neuron.html">00359</a> <span class="keyword">class </span><a class="code" href="classneuralpp_1_1Neuron.html" title="Class for managing neurons.">Neuron</a> {
<a name="l00360"></a><a class="code" href="classneuralpp_1_1Neuron.html#eec680c47272b2465e8d8a998c359853">00360</a> <span class="keywordtype">double</span> <a class="code" href="classneuralpp_1_1Neuron.html#eec680c47272b2465e8d8a998c359853">actv_val</a>;
<a name="l00361"></a><a class="code" href="classneuralpp_1_1Neuron.html#da75259de98b1a893c736666af6bfdc3">00361</a> <span class="keywordtype">double</span> <a class="code" href="classneuralpp_1_1Neuron.html#da75259de98b1a893c736666af6bfdc3">prop_val</a>;
<a name="l00362"></a><a class="code" href="classneuralpp_1_1Neuron.html#7b16632868821d73dedcb8edaf6dbbef">00362</a> <span class="keywordtype">double</span> <a class="code" href="classneuralpp_1_1Neuron.html#7b16632868821d73dedcb8edaf6dbbef">threshold</a>;
<a name="l00363"></a>00363
<a name="l00364"></a><a class="code" href="classneuralpp_1_1Neuron.html#bd07357465bb7b29bb344400e9e08710">00364</a> std::vector&lt; Synapsis &gt; <a class="code" href="classneuralpp_1_1Neuron.html#bd07357465bb7b29bb344400e9e08710">in</a>;
<a name="l00365"></a><a class="code" href="classneuralpp_1_1Neuron.html#982aceef324b7764e778d5949720bc55">00365</a> std::vector&lt; Synapsis &gt; <a class="code" href="classneuralpp_1_1Neuron.html#982aceef324b7764e778d5949720bc55">out</a>;
<a name="l00366"></a>00366
<a name="l00367"></a>00367 double (*<a class="code" href="classneuralpp_1_1Neuron.html#198ddd0d11a26d0052d52b787d6a0df0">actv_f</a>)(double);
<a name="l00368"></a>00368
<a name="l00369"></a>00369 <span class="keyword">public</span>:
<a name="l00376"></a>00376 <a class="code" href="classneuralpp_1_1Neuron.html#c9bd4f5f618fcf1adcebf1ab63ee0960" title="Constructor.">Neuron</a> (<span class="keywordtype">double</span> (*a)(<span class="keywordtype">double</span>), <span class="keywordtype">double</span> th = 0.0);
<a name="l00377"></a>00377
<a name="l00386"></a>00386 <a class="code" href="classneuralpp_1_1Neuron.html#c9bd4f5f618fcf1adcebf1ab63ee0960" title="Constructor.">Neuron</a> (std::vector&lt;Synapsis&gt; <a class="code" href="classneuralpp_1_1Neuron.html#bd07357465bb7b29bb344400e9e08710">in</a>, std::vector&lt;Synapsis&gt; <a class="code" href="classneuralpp_1_1Neuron.html#982aceef324b7764e778d5949720bc55">out</a>,
<a name="l00387"></a>00387 <span class="keywordtype">double</span> (*a)(<span class="keywordtype">double</span>), <span class="keywordtype">double</span> th = 0.0);
<a name="l00388"></a>00388
<a name="l00394"></a>00394 <a class="code" href="classneuralpp_1_1Synapsis.html" title="Class for managing synapsis.">Synapsis</a>&amp; <a class="code" href="classneuralpp_1_1Neuron.html#29f2d9dcc4ca34f224d4dc39bb2f180a" title="Get the i-th synapsis connected on the input of the neuron.">synIn</a> (<span class="keywordtype">size_t</span> i);
<a name="l00395"></a>00395
<a name="l00401"></a>00401 <a class="code" href="classneuralpp_1_1Synapsis.html" title="Class for managing synapsis.">Synapsis</a>&amp; <a class="code" href="classneuralpp_1_1Neuron.html#655f1637e1b754461413ac7fc2ffeebe" title="Get the i-th synapsis connected on the output of the neuron.">synOut</a> (<span class="keywordtype">size_t</span> i);
<a name="l00402"></a>00402
<a name="l00407"></a>00407 <span class="keywordtype">void</span> <a class="code" href="classneuralpp_1_1Neuron.html#4d252151c35839975838539d846d70be" title="It pushes a new input synapsis.">push_in</a> (<a class="code" href="classneuralpp_1_1Synapsis.html" title="Class for managing synapsis.">Synapsis</a> s);
<a name="l00408"></a>00408
<a name="l00413"></a>00413 <span class="keywordtype">void</span> <a class="code" href="classneuralpp_1_1Neuron.html#2c0acb0e6d413c4e0fc9e7939da1a684" title="It pushes a new output synapsis.">push_out</a> (<a class="code" href="classneuralpp_1_1Synapsis.html" title="Class for managing synapsis.">Synapsis</a> s);
<a name="l00414"></a>00414
<a name="l00419"></a>00419 <span class="keywordtype">void</span> <a class="code" href="classneuralpp_1_1Neuron.html#ddf00ffef030b27ed11901aad08822bd" title="Change the activation value of the neuron.">setActv</a> (<span class="keywordtype">double</span> a);
<a name="l00420"></a>00420
<a name="l00425"></a>00425 <span class="keywordtype">void</span> <a class="code" href="classneuralpp_1_1Neuron.html#aa6e58f073a76b3481fea9115a4e6ea6" title="Change the propagation value of the neuron.">setProp</a> (<span class="keywordtype">double</span> p);
<a name="l00426"></a>00426
<a name="l00431"></a>00431 <span class="keywordtype">double</span> <a class="code" href="classneuralpp_1_1Neuron.html#55993867179f0ac7d1e0e2c460ceb611" title="Get the activation value of the neuron.">getActv</a>();
<a name="l00432"></a>00432
<a name="l00437"></a>00437 <span class="keywordtype">double</span> <a class="code" href="classneuralpp_1_1Neuron.html#57c022f82213f662e2a263fc134a3fc9" title="Get the propagation value of the neuron.">getProp</a>();
<a name="l00438"></a>00438
<a name="l00442"></a>00442 <span class="keywordtype">void</span> <a class="code" href="classneuralpp_1_1Neuron.html#928d9bf5aed600119c640779e4034f30" title="Compute the propagation value of the neuron and set it.">propagate</a>();
<a name="l00443"></a>00443
<a name="l00448"></a>00448 <span class="keywordtype">size_t</span> <a class="code" href="classneuralpp_1_1Neuron.html#ad97f1a082d5f969eb4c69ab454ecfbb" title="Get the number of input synapsis for the neuron.">nIn</a>();
<a name="l00449"></a>00449
<a name="l00454"></a>00454 <span class="keywordtype">size_t</span> <a class="code" href="classneuralpp_1_1Neuron.html#fe458021e3b20d58dc608fb94ae2135b" title="Get the number of output synapsis for the neuron.">nOut</a>();
<a name="l00455"></a>00455
<a name="l00459"></a>00459 <span class="keywordtype">void</span> <a class="code" href="classneuralpp_1_1Neuron.html#2e2ccb69277fc3d992a3a3f2360ed154" title="Remove input and output synapsis from a neuron.">synClear</a>();
<a name="l00460"></a>00460 };
<a name="l00461"></a>00461
<a name="l00467"></a><a class="code" href="classneuralpp_1_1Layer.html">00467</a> <span class="keyword">class </span><a class="code" href="classneuralpp_1_1Layer.html" title="Class for managing layers of neurons.">Layer</a> {
<a name="l00468"></a><a class="code" href="classneuralpp_1_1Layer.html#8188cb5c264e6021cee9979b968a0305">00468</a> std::vector&lt;Neuron&gt; <a class="code" href="classneuralpp_1_1Layer.html#8188cb5c264e6021cee9979b968a0305">elements</a>;
<a name="l00469"></a><a class="code" href="classneuralpp_1_1Layer.html#02cf4efe1da02a7404d25375c85ed71f">00469</a> <span class="keywordtype">double</span> <a class="code" href="classneuralpp_1_1Layer.html#02cf4efe1da02a7404d25375c85ed71f">threshold</a>;
<a name="l00470"></a>00470
<a name="l00471"></a>00471 void (*<a class="code" href="classneuralpp_1_1Layer.html#c023a15a16353d0b4f44060a159f550f">update_weights</a>)();
<a name="l00472"></a>00472 double (*<a class="code" href="classneuralpp_1_1Layer.html#824367da29f92253a027a7c5b4a4405e">actv_f</a>)(double);
<a name="l00473"></a>00473
<a name="l00478"></a>00478 <span class="keywordtype">void</span> <a class="code" href="classneuralpp_1_1Layer.html#dbad95f635343a2998794113d7762cf7" title="It sets a vector of propagation values to all its neurons.">setProp</a> (vector&lt;double&gt;&amp; v);
<a name="l00479"></a>00479
<a name="l00484"></a>00484 <span class="keywordtype">void</span> <a class="code" href="classneuralpp_1_1Layer.html#98f79281b680b1d18fd91fa5794c0899" title="It sets a vector of activation values to all its neurons.">setActv</a> (vector&lt;double&gt;&amp; v);
<a name="l00485"></a>00485
<a name="l00489"></a>00489 <span class="keywordtype">void</span> <a class="code" href="classneuralpp_1_1Layer.html#fcfd306039dbaf91c9e2dcc8fc1f1ce1" title="It propagates its activation values to the output layers.">propagate</a>();
<a name="l00490"></a>00490
<a name="l00494"></a>00494 <span class="keywordtype">size_t</span> <a class="code" href="classneuralpp_1_1Layer.html#7ca71ed62fbe9c1e9c0fb6a8dcaf76f0">size</a>() <span class="keyword">const</span>;
<a name="l00495"></a>00495 };
<a name="l00496"></a>00496
<a name="l00497"></a><a class="code" href="structneuralpp_1_1netrecord.html">00497</a> <span class="keyword">struct </span><a class="code" href="structneuralpp_1_1netrecord.html">netrecord</a> {
<a name="l00498"></a><a class="code" href="structneuralpp_1_1netrecord.html#e1f480bfef05033accef40f77c09fa87">00498</a> <span class="keywordtype">int</span> <a class="code" href="structneuralpp_1_1netrecord.html#e1f480bfef05033accef40f77c09fa87">input_size</a>;
<a name="l00499"></a><a class="code" href="structneuralpp_1_1netrecord.html#3c1728ac66c37f6ac85c404d4f55552e">00499</a> <span class="keywordtype">int</span> hidden_size;
<a name="l00500"></a><a class="code" href="structneuralpp_1_1netrecord.html#95f2b0651dd3a0e5e7201ff354e401b4">00500</a> <span class="keywordtype">int</span> <a class="code" href="structneuralpp_1_1netrecord.html#95f2b0651dd3a0e5e7201ff354e401b4">output_size</a>;
<a name="l00501"></a>00501
<a name="l00502"></a><a class="code" href="structneuralpp_1_1netrecord.html#ab0149ed5ea0694e88213a07cd4427d1">00502</a> <span class="keywordtype">int</span> <a class="code" href="structneuralpp_1_1netrecord.html#ab0149ed5ea0694e88213a07cd4427d1">epochs</a>;
<a name="l00503"></a><a class="code" href="structneuralpp_1_1netrecord.html#a4f793a39a40144e811fef4d3d2d2b30">00503</a> <span class="keywordtype">double</span> <a class="code" href="structneuralpp_1_1netrecord.html#a4f793a39a40144e811fef4d3d2d2b30">l_rate</a>;
<a name="l00504"></a><a class="code" href="structneuralpp_1_1netrecord.html#dcc44fde3f67058d26ef2d5cbd0904e6">00504</a> <span class="keywordtype">double</span> <a class="code" href="structneuralpp_1_1netrecord.html#dcc44fde3f67058d26ef2d5cbd0904e6">ex</a>;
<a name="l00505"></a>00505 };
<a name="l00474"></a>00474 <span class="keyword">public</span>:
<a name="l00482"></a>00482 <a class="code" href="classneuralpp_1_1Layer.html#a235767701b5e9dcf28c5e9e0d04cb0b" title="Constructor.">Layer</a> (<span class="keywordtype">size_t</span> sz, <span class="keywordtype">double</span> (*a)(<span class="keywordtype">double</span>), <span class="keywordtype">double</span> th = 0.0);
<a name="l00483"></a>00483
<a name="l00492"></a>00492 <a class="code" href="classneuralpp_1_1Layer.html#a235767701b5e9dcf28c5e9e0d04cb0b" title="Constructor.">Layer</a> (std::vector&lt;Neuron&gt;&amp; neurons, <span class="keywordtype">double</span>(*a)(<span class="keywordtype">double</span>), <span class="keywordtype">double</span> th = 0.0);
<a name="l00493"></a>00493
<a name="l00499"></a>00499 <a class="code" href="classneuralpp_1_1Neuron.html" title="Class for managing neurons.">Neuron</a>&amp; <a class="code" href="classneuralpp_1_1Layer.html#45ff7554830558155c6fbce3b6827122" title="Redefinition for operator [].">operator[] </a>(<span class="keywordtype">size_t</span> i) <span class="keywordflow">throw</span>(<a class="code" href="classneuralpp_1_1NetworkIndexOutOfBoundsException.html" title="Exception raised when trying to access a neuron whose index is larger than the number...">NetworkIndexOutOfBoundsException</a>);
<a name="l00500"></a>00500
<a name="l00505"></a>00505 <span class="keywordtype">void</span> <a class="code" href="classneuralpp_1_1Layer.html#ac33444fde14633fa1ad4acb024ad150" title="It links a layer to another.">link</a> (<a class="code" href="classneuralpp_1_1Layer.html" title="Class for managing layers of neurons.">Layer</a>&amp; l);
<a name="l00506"></a>00506
<a name="l00507"></a><a class="code" href="structneuralpp_1_1neuronrecord.html">00507</a> <span class="keyword">struct </span><a class="code" href="structneuralpp_1_1neuronrecord.html">neuronrecord</a> {
<a name="l00508"></a><a class="code" href="structneuralpp_1_1neuronrecord.html#30b298a95939b88b565fefc2dc57e89d">00508</a> <span class="keywordtype">double</span> <a class="code" href="structneuralpp_1_1neuronrecord.html#30b298a95939b88b565fefc2dc57e89d">prop</a>;
<a name="l00509"></a><a class="code" href="structneuralpp_1_1neuronrecord.html#15201b190584987255d81d4b7e773375">00509</a> <span class="keywordtype">double</span> <a class="code" href="structneuralpp_1_1neuronrecord.html#15201b190584987255d81d4b7e773375">actv</a>;
<a name="l00510"></a>00510 };
<a name="l00511"></a>00511
<a name="l00512"></a><a class="code" href="structneuralpp_1_1synrecord.html">00512</a> <span class="keyword">struct </span><a class="code" href="structneuralpp_1_1synrecord.html">synrecord</a> {
<a name="l00513"></a><a class="code" href="structneuralpp_1_1synrecord.html#81a7dbc97eecbf5bc85cac46373a78d2">00513</a> <span class="keywordtype">double</span> w;
<a name="l00514"></a><a class="code" href="structneuralpp_1_1synrecord.html#3a862082dfa0edffce84936818bab374">00514</a> <span class="keywordtype">double</span> <a class="code" href="structneuralpp_1_1synrecord.html#3a862082dfa0edffce84936818bab374">d</a>;
<a name="l00515"></a>00515 };
<a name="l00516"></a>00516 }
<a name="l00511"></a>00511 <span class="keywordtype">void</span> <a class="code" href="classneuralpp_1_1Layer.html#88ceffc23f02a9dc24d4355767b7cca7" title="Set the input values for the neurons of the layer (just use it for the input layer)...">setInput</a> (std::vector&lt;double&gt; v);
<a name="l00512"></a>00512
<a name="l00516"></a>00516 <span class="keywordtype">void</span> <a class="code" href="classneuralpp_1_1Layer.html#fcfd306039dbaf91c9e2dcc8fc1f1ce1" title="It propagates its activation values to the output layers.">propagate</a>();
<a name="l00517"></a>00517
<a name="l00518"></a>00518 <span class="comment">//#endif</span>
<a name="l00519"></a>00519 <span class="preprocessor">#endif</span>
<a name="l00520"></a>00520 <span class="preprocessor"></span>
<a name="l00521"></a>00521 <span class="keywordtype">size_t</span> <a class="code" href="classneuralpp_1_1Layer.html#7ca71ed62fbe9c1e9c0fb6a8dcaf76f0">size</a>() <span class="keyword">const</span>;
<a name="l00522"></a>00522 };
<a name="l00523"></a>00523
<a name="l00524"></a><a class="code" href="structneuralpp_1_1netrecord.html">00524</a> <span class="keyword">struct </span><a class="code" href="structneuralpp_1_1netrecord.html">netrecord</a> {
<a name="l00525"></a><a class="code" href="structneuralpp_1_1netrecord.html#e1f480bfef05033accef40f77c09fa87">00525</a> <span class="keywordtype">int</span> <a class="code" href="structneuralpp_1_1netrecord.html#e1f480bfef05033accef40f77c09fa87">input_size</a>;
<a name="l00526"></a><a class="code" href="structneuralpp_1_1netrecord.html#3c1728ac66c37f6ac85c404d4f55552e">00526</a> <span class="keywordtype">int</span> hidden_size;
<a name="l00527"></a><a class="code" href="structneuralpp_1_1netrecord.html#95f2b0651dd3a0e5e7201ff354e401b4">00527</a> <span class="keywordtype">int</span> <a class="code" href="structneuralpp_1_1netrecord.html#95f2b0651dd3a0e5e7201ff354e401b4">output_size</a>;
<a name="l00528"></a>00528
<a name="l00529"></a><a class="code" href="structneuralpp_1_1netrecord.html#ab0149ed5ea0694e88213a07cd4427d1">00529</a> <span class="keywordtype">int</span> <a class="code" href="structneuralpp_1_1netrecord.html#ab0149ed5ea0694e88213a07cd4427d1">epochs</a>;
<a name="l00530"></a><a class="code" href="structneuralpp_1_1netrecord.html#a4f793a39a40144e811fef4d3d2d2b30">00530</a> <span class="keywordtype">double</span> <a class="code" href="structneuralpp_1_1netrecord.html#a4f793a39a40144e811fef4d3d2d2b30">l_rate</a>;
<a name="l00531"></a><a class="code" href="structneuralpp_1_1netrecord.html#dcc44fde3f67058d26ef2d5cbd0904e6">00531</a> <span class="keywordtype">double</span> <a class="code" href="structneuralpp_1_1netrecord.html#dcc44fde3f67058d26ef2d5cbd0904e6">ex</a>;
<a name="l00532"></a>00532 };
<a name="l00533"></a>00533
<a name="l00534"></a><a class="code" href="structneuralpp_1_1neuronrecord.html">00534</a> <span class="keyword">struct </span><a class="code" href="structneuralpp_1_1neuronrecord.html">neuronrecord</a> {
<a name="l00535"></a><a class="code" href="structneuralpp_1_1neuronrecord.html#30b298a95939b88b565fefc2dc57e89d">00535</a> <span class="keywordtype">double</span> prop;
<a name="l00536"></a><a class="code" href="structneuralpp_1_1neuronrecord.html#15201b190584987255d81d4b7e773375">00536</a> <span class="keywordtype">double</span> <a class="code" href="structneuralpp_1_1neuronrecord.html#15201b190584987255d81d4b7e773375">actv</a>;
<a name="l00537"></a>00537 };
<a name="l00538"></a>00538
<a name="l00539"></a><a class="code" href="structneuralpp_1_1synrecord.html">00539</a> <span class="keyword">struct </span><a class="code" href="structneuralpp_1_1synrecord.html">synrecord</a> {
<a name="l00540"></a><a class="code" href="structneuralpp_1_1synrecord.html#81a7dbc97eecbf5bc85cac46373a78d2">00540</a> <span class="keywordtype">double</span> w;
<a name="l00541"></a><a class="code" href="structneuralpp_1_1synrecord.html#3a862082dfa0edffce84936818bab374">00541</a> <span class="keywordtype">double</span> <a class="code" href="structneuralpp_1_1synrecord.html#3a862082dfa0edffce84936818bab374">d</a>;
<a name="l00542"></a>00542 };
<a name="l00543"></a>00543 }
<a name="l00544"></a>00544
<a name="l00545"></a>00545 <span class="preprocessor">#endif</span>
<a name="l00546"></a>00546 <span class="preprocessor"></span>
</pre></div></div>
<hr size="1"><address style="text-align: right;"><small>Generated on Sat Aug 15 02:56:02 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<a href="http://www.doxygen.org/index.html">
<img src="doxygen.png" alt="doxygen" align="middle" border="0"></a> 1.5.6 </small></address>
</body>

View file

@ -12,6 +12,7 @@
<li><a href="namespaces.html"><span>Namespaces</span></a></li>
<li><a href="annotated.html"><span>Classes</span></a></li>
<li class="current"><a href="files.html"><span>Files</span></a></li>
<li><a href="examples.html"><span>Examples</span></a></li>
</ul>
</div>
</div>
@ -50,12 +51,14 @@
<tr><td class="memItemLeft" nowrap align="right" valign="top">#define&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="neural_09_09_8hpp.html#839a9222721835f53c5b248241f535f4">RAND</a>&nbsp;&nbsp;&nbsp;(double) ( (rand() / (RAND_MAX/2)) - 1)</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Default rand value: |sin(rand)|, always &gt;= 0 and &lt;= 1. <a href="#839a9222721835f53c5b248241f535f4"></a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">#define&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="neural_09_09_8hpp.html#05e2bb5b9fc32f0b6b4d84fe43177d72">BETA0</a>&nbsp;&nbsp;&nbsp;0.8</td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">#define&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="neural_09_09_8hpp.html#05e2bb5b9fc32f0b6b4d84fe43177d72">BETA0</a>&nbsp;&nbsp;&nbsp;1.0</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Initial value for the inertial momentum of the synapses. <a href="#05e2bb5b9fc32f0b6b4d84fe43177d72"></a><br></td></tr>
<tr><td colspan="2"><br><h2>Functions</h2></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">double&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespaceneuralpp.html#43c8197cc83f65fa9676386579671aec">neuralpp::df</a> (double(*f)(double), double x)</td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">double&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespaceneuralpp.html#7df3a0de999c7a635f2289749ed4f194">neuralpp::__actv</a> (double prop)</td></tr>
</table>
<hr><h2>Define Documentation</h2>
<a class="anchor" name="05e2bb5b9fc32f0b6b4d84fe43177d72"></a><!-- doxytag: member="neural++.hpp::BETA0" ref="05e2bb5b9fc32f0b6b4d84fe43177d72" args="" -->
@ -63,7 +66,7 @@
<div class="memproto">
<table class="memname">
<tr>
<td class="memname">#define BETA0&nbsp;&nbsp;&nbsp;0.8 </td>
<td class="memname">#define BETA0&nbsp;&nbsp;&nbsp;1.0 </td>
</tr>
</table>
</div>
@ -93,7 +96,7 @@ Default rand value: |sin(rand)|, always &gt;= 0 and &lt;= 1.
</div>
</div><p>
</div>
<hr size="1"><address style="text-align: right;"><small>Generated on Sat Aug 15 02:56:02 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<a href="http://www.doxygen.org/index.html">
<img src="doxygen.png" alt="doxygen" align="middle" border="0"></a> 1.5.6 </small></address>
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@ -12,10 +12,11 @@
<li><a href="namespaces.html"><span>Namespaces</span></a></li>
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<li><a href="examples.html"><span>Examples</span></a></li>
</ul>
</div>
<h1>neural++_exception.hpp</h1><a href="neural_09_09__exception_8hpp.html">Go to the documentation of this file.</a><div class="fragment"><pre class="fragment"><a name="l00001"></a>00001 <span class="comment">/**************************************************************************************************</span>
<a name="l00002"></a>00002 <span class="comment"> * LibNeural++ v.0.2 - All-purpose library for managing neural networks *</span>
<a name="l00002"></a>00002 <span class="comment"> * LibNeural++ v.0.4 - All-purpose library for managing neural networks *</span>
<a name="l00003"></a>00003 <span class="comment"> * Copyright (C) 2009, BlackLight *</span>
<a name="l00004"></a>00004 <span class="comment"> * *</span>
<a name="l00005"></a>00005 <span class="comment"> * This program is free software: you can redistribute it and/or modify it under the terms of the *</span>
@ -27,52 +28,47 @@
<a name="l00011"></a>00011 <span class="comment"> * this program. If not, see &lt;http://www.gnu.org/licenses/&gt;. *</span>
<a name="l00012"></a>00012 <span class="comment"> **************************************************************************************************/</span>
<a name="l00013"></a>00013
<a name="l00014"></a>00014 <span class="preprocessor">#ifndef __cplusplus</span>
<a name="l00015"></a>00015 <span class="preprocessor"></span><span class="preprocessor">#error "This is a C++ library, you know, so you'd better use a C++ compiler to compile it"</span>
<a name="l00016"></a>00016 <span class="preprocessor"></span><span class="preprocessor">#else</span>
<a name="l00017"></a>00017 <span class="preprocessor"></span>
<a name="l00018"></a>00018 <span class="preprocessor">#ifndef __NEURALPP_EXCEPTION</span>
<a name="l00019"></a>00019 <span class="preprocessor"></span><span class="preprocessor">#define __NEURALPP_EXCEPTION</span>
<a name="l00020"></a>00020 <span class="preprocessor"></span>
<a name="l00021"></a>00021 <span class="preprocessor">#include &lt;exception&gt;</span>
<a name="l00022"></a>00022
<a name="l00023"></a>00023 <span class="keyword">namespace </span>neuralpp {
<a name="l00028"></a>00028 <span class="keyword">class </span>NetworkFileNotFoundException : <span class="keyword">public</span> std::exception {
<a name="l00029"></a>00029 <span class="keyword">public</span>:
<a name="l00030"></a>00030 NetworkFileNotFoundException() {}
<a name="l00031"></a>00031 <span class="keyword">const</span> <span class="keywordtype">char</span>* what() <span class="keyword">const</span> throw() { <span class="keywordflow">return</span> <span class="stringliteral">"Attempt to load a neural network from an invalid network file"</span>; }
<a name="l00032"></a>00032 };
<a name="l00033"></a>00033
<a name="l00039"></a>00039 <span class="keyword">class </span>NetworkFileWriteException : <span class="keyword">public</span> std::exception {
<a name="l00040"></a>00040 <span class="keyword">public</span>:
<a name="l00041"></a>00041 NetworkFileWriteException() {}
<a name="l00042"></a>00042 <span class="keyword">const</span> <span class="keywordtype">char</span>* what() <span class="keyword">const</span> throw() { <span class="keywordflow">return</span> <span class="stringliteral">"There was an error while writing the network file"</span>; }
<a name="l00043"></a>00043 };
<a name="l00044"></a>00044
<a name="l00049"></a>00049 <span class="keyword">class </span>InvalidXMLException : <span class="keyword">public</span> std::exception {
<a name="l00050"></a>00050 <span class="keyword">public</span>:
<a name="l00051"></a>00051 InvalidXMLException() {}
<a name="l00052"></a>00052 <span class="keyword">const</span> <span class="keywordtype">char</span>* what() <span class="keyword">const</span> throw() { <span class="keywordflow">return</span> <span class="stringliteral">"Attempt to load an invalid XML file"</span>; }
<a name="l00053"></a>00053 };
<a name="l00054"></a>00054
<a name="l00060"></a>00060 <span class="keyword">class </span>NetworkIndexOutOfBoundsException : <span class="keyword">public</span> std::exception {
<a name="l00061"></a>00061 <span class="keyword">public</span>:
<a name="l00062"></a>00062 NetworkIndexOutOfBoundsException() {}
<a name="l00063"></a>00063 <span class="keyword">const</span> <span class="keywordtype">char</span>* what() <span class="keyword">const</span> throw() { <span class="keywordflow">return</span> <span class="stringliteral">"Attempt to access a non-existing neuron"</span>; }
<a name="l00064"></a>00064 };
<a name="l00065"></a>00065
<a name="l00071"></a>00071 <span class="keyword">class </span>InvalidSynapticalWeightException : <span class="keyword">public</span> std::exception {
<a name="l00072"></a>00072 <span class="keyword">public</span>:
<a name="l00073"></a>00073 InvalidSynapticalWeightException() {}
<a name="l00074"></a>00074 <span class="keyword">const</span> <span class="keywordtype">char</span>* what() <span class="keyword">const</span> throw() { <span class="keywordflow">return</span> <span class="stringliteral">"Attempt to set an invalid weight for the synapsis"</span>; }
<a name="l00075"></a>00075 };
<a name="l00076"></a>00076 }
<a name="l00077"></a>00077
<a name="l00078"></a>00078 <span class="preprocessor">#endif</span>
<a name="l00079"></a>00079 <span class="preprocessor"></span><span class="preprocessor">#endif</span>
<a name="l00080"></a>00080 <span class="preprocessor"></span>
<a name="l00014"></a>00014 <span class="preprocessor">#ifndef __NEURALPP_EXCEPTION</span>
<a name="l00015"></a>00015 <span class="preprocessor"></span><span class="preprocessor">#define __NEURALPP_EXCEPTION</span>
<a name="l00016"></a>00016 <span class="preprocessor"></span>
<a name="l00017"></a>00017 <span class="preprocessor">#include &lt;exception&gt;</span>
<a name="l00018"></a>00018
<a name="l00019"></a>00019 <span class="keyword">namespace </span>neuralpp {
<a name="l00024"></a><a class="code" href="classneuralpp_1_1NetworkFileNotFoundException.html">00024</a> <span class="keyword">class </span><a class="code" href="classneuralpp_1_1NetworkFileNotFoundException.html" title="Exception thrown when doing an attempt to load a network from an invalid file.">NetworkFileNotFoundException</a> : <span class="keyword">public</span> std::exception {
<a name="l00025"></a>00025 <span class="keyword">public</span>:
<a name="l00026"></a><a class="code" href="classneuralpp_1_1NetworkFileNotFoundException.html#9603eebdb841f06c9b1007e65cba60f6">00026</a> <a class="code" href="classneuralpp_1_1NetworkFileNotFoundException.html#9603eebdb841f06c9b1007e65cba60f6">NetworkFileNotFoundException</a>() {}
<a name="l00027"></a><a class="code" href="classneuralpp_1_1NetworkFileNotFoundException.html#24cde7729ab22d343f36e638cfc40702">00027</a> <span class="keyword">const</span> <span class="keywordtype">char</span>* <a class="code" href="classneuralpp_1_1NetworkFileNotFoundException.html#24cde7729ab22d343f36e638cfc40702">what</a>() <span class="keyword">const</span> throw() { <span class="keywordflow">return</span> <span class="stringliteral">"Attempt to load a neural network from an invalid network file"</span>; }
<a name="l00028"></a>00028 };
<a name="l00029"></a>00029
<a name="l00035"></a><a class="code" href="classneuralpp_1_1NetworkFileWriteException.html">00035</a> <span class="keyword">class </span><a class="code" href="classneuralpp_1_1NetworkFileWriteException.html" title="Exception thrown when trying to write the network&amp;#39;s information to a file that...">NetworkFileWriteException</a> : <span class="keyword">public</span> std::exception {
<a name="l00036"></a>00036 <span class="keyword">public</span>:
<a name="l00037"></a><a class="code" href="classneuralpp_1_1NetworkFileWriteException.html#83bc897b0ea11a384e0839a39e9fdb48">00037</a> <a class="code" href="classneuralpp_1_1NetworkFileWriteException.html#83bc897b0ea11a384e0839a39e9fdb48">NetworkFileWriteException</a>() {}
<a name="l00038"></a><a class="code" href="classneuralpp_1_1NetworkFileWriteException.html#c8802852cb38d5edf6f490ff3acb6078">00038</a> <span class="keyword">const</span> <span class="keywordtype">char</span>* <a class="code" href="classneuralpp_1_1NetworkFileWriteException.html#c8802852cb38d5edf6f490ff3acb6078">what</a>() <span class="keyword">const</span> throw() { <span class="keywordflow">return</span> <span class="stringliteral">"There was an error while writing the network file"</span>; }
<a name="l00039"></a>00039 };
<a name="l00040"></a>00040
<a name="l00045"></a><a class="code" href="classneuralpp_1_1InvalidXMLException.html">00045</a> <span class="keyword">class </span><a class="code" href="classneuralpp_1_1InvalidXMLException.html" title="Exception thrown when trying parsing an invalid XML.">InvalidXMLException</a> : <span class="keyword">public</span> std::exception {
<a name="l00046"></a>00046 <span class="keyword">public</span>:
<a name="l00047"></a><a class="code" href="classneuralpp_1_1InvalidXMLException.html#10279e6f42a1ccb934afcfef2770c537">00047</a> <a class="code" href="classneuralpp_1_1InvalidXMLException.html#10279e6f42a1ccb934afcfef2770c537">InvalidXMLException</a>() {}
<a name="l00048"></a><a class="code" href="classneuralpp_1_1InvalidXMLException.html#4a8b81678ed0c319e1715ab5ef9112da">00048</a> <span class="keyword">const</span> <span class="keywordtype">char</span>* <a class="code" href="classneuralpp_1_1InvalidXMLException.html#4a8b81678ed0c319e1715ab5ef9112da">what</a>() <span class="keyword">const</span> throw() { <span class="keywordflow">return</span> <span class="stringliteral">"Attempt to load an invalid XML file"</span>; }
<a name="l00049"></a>00049 };
<a name="l00050"></a>00050
<a name="l00056"></a><a class="code" href="classneuralpp_1_1NetworkIndexOutOfBoundsException.html">00056</a> <span class="keyword">class </span><a class="code" href="classneuralpp_1_1NetworkIndexOutOfBoundsException.html" title="Exception raised when trying to access a neuron whose index is larger than the number...">NetworkIndexOutOfBoundsException</a> : <span class="keyword">public</span> std::exception {
<a name="l00057"></a>00057 <span class="keyword">public</span>:
<a name="l00058"></a><a class="code" href="classneuralpp_1_1NetworkIndexOutOfBoundsException.html#07141d2225ea9f2d486e755a3660d594">00058</a> <a class="code" href="classneuralpp_1_1NetworkIndexOutOfBoundsException.html#07141d2225ea9f2d486e755a3660d594">NetworkIndexOutOfBoundsException</a>() {}
<a name="l00059"></a><a class="code" href="classneuralpp_1_1NetworkIndexOutOfBoundsException.html#8b65d77cb375a0aa40d5a9ea692bd5c3">00059</a> <span class="keyword">const</span> <span class="keywordtype">char</span>* <a class="code" href="classneuralpp_1_1NetworkIndexOutOfBoundsException.html#8b65d77cb375a0aa40d5a9ea692bd5c3">what</a>() <span class="keyword">const</span> throw() { <span class="keywordflow">return</span> <span class="stringliteral">"Attempt to access a non-existing neuron"</span>; }
<a name="l00060"></a>00060 };
<a name="l00061"></a>00061
<a name="l00067"></a><a class="code" href="classneuralpp_1_1InvalidSynapticalWeightException.html">00067</a> <span class="keyword">class </span><a class="code" href="classneuralpp_1_1InvalidSynapticalWeightException.html" title="Exception raised when, while trying the network or directly, the weight of a synapsis...">InvalidSynapticalWeightException</a> : <span class="keyword">public</span> std::exception {
<a name="l00068"></a>00068 <span class="keyword">public</span>:
<a name="l00069"></a><a class="code" href="classneuralpp_1_1InvalidSynapticalWeightException.html#42e54de0ef9d9f711a483287f4f95916">00069</a> <a class="code" href="classneuralpp_1_1InvalidSynapticalWeightException.html#42e54de0ef9d9f711a483287f4f95916">InvalidSynapticalWeightException</a>() {}
<a name="l00070"></a><a class="code" href="classneuralpp_1_1InvalidSynapticalWeightException.html#8d374dd7e8363b2551ae6e306b11473a">00070</a> <span class="keyword">const</span> <span class="keywordtype">char</span>* <a class="code" href="classneuralpp_1_1InvalidSynapticalWeightException.html#8d374dd7e8363b2551ae6e306b11473a">what</a>() <span class="keyword">const</span> throw() { <span class="keywordflow">return</span> <span class="stringliteral">"Attempt to set an invalid weight for the synapsis"</span>; }
<a name="l00071"></a>00071 };
<a name="l00072"></a>00072 }
<a name="l00073"></a>00073
<a name="l00074"></a>00074 <span class="preprocessor">#endif</span>
<a name="l00075"></a>00075 <span class="preprocessor"></span>
</pre></div></div>
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<h1>neural++_exception.hpp File Reference</h1>
<h1>neural++_exception.hpp File Reference</h1><code>#include &lt;exception&gt;</code><br>
<p>
<a href="neural_09_09__exception_8hpp-source.html">Go to the source code of this file.</a><table border="0" cellpadding="0" cellspacing="0">
<tr><td></td></tr>
<tr><td colspan="2"><br><h2>Namespaces</h2></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">namespace &nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespaceneuralpp.html">neuralpp</a></td></tr>
<tr><td colspan="2"><br><h2>Classes</h2></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">class &nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1NetworkFileNotFoundException.html">neuralpp::NetworkFileNotFoundException</a></td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Exception thrown when doing an attempt to load a network from an invalid file. <a href="classneuralpp_1_1NetworkFileNotFoundException.html#_details">More...</a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">class &nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1NetworkFileWriteException.html">neuralpp::NetworkFileWriteException</a></td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Exception thrown when trying to write the network's information to a file that cannot be written. <a href="classneuralpp_1_1NetworkFileWriteException.html#_details">More...</a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">class &nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1InvalidXMLException.html">neuralpp::InvalidXMLException</a></td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Exception thrown when trying parsing an invalid XML. <a href="classneuralpp_1_1InvalidXMLException.html#_details">More...</a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">class &nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1NetworkIndexOutOfBoundsException.html">neuralpp::NetworkIndexOutOfBoundsException</a></td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Exception raised when trying to access a neuron whose index is larger than the number of neurons in the network. <a href="classneuralpp_1_1NetworkIndexOutOfBoundsException.html#_details">More...</a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">class &nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1InvalidSynapticalWeightException.html">neuralpp::InvalidSynapticalWeightException</a></td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Exception raised when, while trying the network or directly, the weight of a synapsis is set to a value |w| &gt; 1. <a href="classneuralpp_1_1InvalidSynapticalWeightException.html#_details">More...</a><br></td></tr>
</table>
</div>
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@ -31,7 +32,7 @@
<tr class="memlist"><td><a class="el" href="structCMarkup_1_1ConvertEncoding.html#8ab5d602610c46eb26d0fbf8a39b2da8">strFromEncoding</a></td><td><a class="el" href="structCMarkup_1_1ConvertEncoding.html">CMarkup::ConvertEncoding</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="structCMarkup_1_1ConvertEncoding.html#cc2420305e7cfa6c9d18f7ce9daa4313">strToEncoding</a></td><td><a class="el" href="structCMarkup_1_1ConvertEncoding.html">CMarkup::ConvertEncoding</a></td><td></td></tr>
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@ -197,7 +198,7 @@
<hr>The documentation for this struct was generated from the following file:<ul>
<li><a class="el" href="Markup_8h-source.html">Markup.h</a></ul>
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<tr class="memlist"><td><a class="el" href="structCMarkup_1_1ElemPos.html#853d5e4a5c6b03643e7210671385896c">StartContent</a>() const </td><td><a class="el" href="structCMarkup_1_1ElemPos.html">CMarkup::ElemPos</a></td><td><code> [inline]</code></td></tr>
<tr class="memlist"><td><a class="el" href="structCMarkup_1_1ElemPos.html#987926f5677976e6288e5b4c3a224d96">StartTagLen</a>() const </td><td><a class="el" href="structCMarkup_1_1ElemPos.html">CMarkup::ElemPos</a></td><td><code> [inline]</code></td></tr>
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@ -527,7 +528,7 @@
<hr>The documentation for this struct was generated from the following file:<ul>
<li><a class="el" href="Markup_8h-source.html">Markup.h</a></ul>
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<tr class="memlist"><td><a class="el" href="structCMarkup_1_1FilePos.html#b507cbd49031186d4b3fbf7d2d009c75">strEncoding</a></td><td><a class="el" href="structCMarkup_1_1FilePos.html">CMarkup::FilePos</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="structCMarkup_1_1FilePos.html#62db77f82233f3244272eb973a9ecfc8">strIOResult</a></td><td><a class="el" href="structCMarkup_1_1FilePos.html">CMarkup::FilePos</a></td><td></td></tr>
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<hr>The documentation for this struct was generated from the following file:<ul>
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<tr class="memlist"><td><a class="el" href="structCMarkup_1_1NodePos.html#c1939dd0ed1d2ecb35eb35bd2e88f69c">nStart</a></td><td><a class="el" href="structCMarkup_1_1NodePos.html">CMarkup::NodePos</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="structCMarkup_1_1NodePos.html#b9b37d8614b6980a935157199558c261">strMeta</a></td><td><a class="el" href="structCMarkup_1_1NodePos.html">CMarkup::NodePos</a></td><td></td></tr>
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<hr>The documentation for this struct was generated from the following file:<ul>
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<tr class="memlist"><td><a class="el" href="structCMarkup_1_1NodeStack.html#4e9aad88e12b7bbabdbb3fd65fc51585">TopIndex</a>()</td><td><a class="el" href="structCMarkup_1_1NodeStack.html">CMarkup::NodeStack</a></td><td><code> [inline]</code></td></tr>
<tr class="memlist"><td><a class="el" href="structCMarkup_1_1NodeStack.html#6bd62bb0b4c4596016a00eade46cd5ca">~NodeStack</a>()</td><td><a class="el" href="structCMarkup_1_1NodeStack.html">CMarkup::NodeStack</a></td><td><code> [inline]</code></td></tr>
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<hr>The documentation for this struct was generated from the following file:<ul>
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<tr class="memlist"><td><a class="el" href="structCMarkup_1_1PosArray.html#0310976aa8e777cb84ab02ddbae8864c">SegsUsed</a>() const </td><td><a class="el" href="structCMarkup_1_1PosArray.html">CMarkup::PosArray</a></td><td><code> [inline]</code></td></tr>
<tr class="memlist"><td><a class="el" href="structCMarkup_1_1PosArray.html#9f26a70cee21e757fe372201c57fc117">~PosArray</a>()</td><td><a class="el" href="structCMarkup_1_1PosArray.html">CMarkup::PosArray</a></td><td><code> [inline]</code></td></tr>
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<hr>The documentation for this struct was generated from the following file:<ul>
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<tr class="memlist"><td><a class="el" href="structCMarkup_1_1SavedPos.html#28ed16429117003133c33fa8fcaa7924bc202c266163ba746501ff656c189bf3">SPM_USED</a> enum value</td><td><a class="el" href="structCMarkup_1_1SavedPos.html">CMarkup::SavedPos</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="structCMarkup_1_1SavedPos.html#3613f5e8854f961ed02173d22099db4c">strName</a></td><td><a class="el" href="structCMarkup_1_1SavedPos.html">CMarkup::SavedPos</a></td><td></td></tr>
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<hr>The documentation for this struct was generated from the following file:<ul>
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<tr class="memlist"><td><a class="el" href="structCMarkup_1_1SavedPosMap.html#681e409f964bbd86a088358dffaeb808">SavedPosMap</a>(int nSize)</td><td><a class="el" href="structCMarkup_1_1SavedPosMap.html">CMarkup::SavedPosMap</a></td><td><code> [inline]</code></td></tr>
<tr class="memlist"><td><a class="el" href="structCMarkup_1_1SavedPosMap.html#b3a7ef305893ba4b6752dea003997c96">~SavedPosMap</a>()</td><td><a class="el" href="structCMarkup_1_1SavedPosMap.html">CMarkup::SavedPosMap</a></td><td><code> [inline]</code></td></tr>
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