Is it time to release 1.0 version?

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blacklight 2009-09-04 11:27:14 +02:00
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<a name="l00644"></a>00644
<a name="l00645"></a>00645 <span class="preprocessor">#endif // !defined(_MARKUP_H_INCLUDED_)</span>
</pre></div></div>
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<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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</div>
</div><p>
</div>
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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<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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<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 2009 for Neural++ by&nbsp;
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<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>
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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<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>
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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<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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@ -84,7 +84,7 @@ Exception raised when, while trying the network or directly, the weight of a syn
<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;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 2009 for Neural++ by&nbsp;
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</div>
<div class="contents">
<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#e0c63b17f7b5b0df20d8361bc9ee92b4">error</a></td><td><a class="el" href="classneuralpp_1_1InvalidXMLException.html">neuralpp::InvalidXMLException</a></td><td><code> [private]</code></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1InvalidXMLException.html#793d311be88606908abf8c5be1348586">InvalidXMLException</a>(const char *err=&quot; &quot;)</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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<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 2009 for Neural++ by&nbsp;
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<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">&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1InvalidXMLException.html#793d311be88606908abf8c5be1348586">InvalidXMLException</a> (const char *err=&quot; &quot;)</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>
<tr><td colspan="2"><br><h2>Private Attributes</h2></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">char *&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1InvalidXMLException.html#e0c63b17f7b5b0df20d8361bc9ee92b4">error</a></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="()" -->
<a class="anchor" name="793d311be88606908abf8c5be1348586"></a><!-- doxytag: member="neuralpp::InvalidXMLException::InvalidXMLException" ref="793d311be88606908abf8c5be1348586" args="(const char *err=&quot; &quot;)" -->
<div class="memitem">
<div class="memproto">
<table class="memname">
<tr>
<td class="memname">neuralpp::InvalidXMLException::InvalidXMLException </td>
<td>(</td>
<td class="paramname"> </td>
<td class="paramtype">const char *&nbsp;</td>
<td class="paramname"> <em>err</em> = <code>&quot;&nbsp;&quot;</code> </td>
<td>&nbsp;)&nbsp;</td>
<td><code> [inline]</code></td>
</tr>
@ -59,6 +63,8 @@ Exception thrown when trying parsing an invalid XML. <hr><h2>Constructor &amp; D
<p>
<p>References <a class="el" href="neural_09_09__exception_8hpp-source.html#l00048">error</a>.</p>
</div>
</div><p>
<hr><h2>Member Function Documentation</h2>
@ -79,12 +85,32 @@ Exception thrown when trying parsing an invalid XML. <hr><h2>Constructor &amp; D
<p>
<p>References <a class="el" href="neural_09_09__exception_8hpp-source.html#l00048">error</a>.</p>
</div>
</div><p>
<hr><h2>Member Data Documentation</h2>
<a class="anchor" name="e0c63b17f7b5b0df20d8361bc9ee92b4"></a><!-- doxytag: member="neuralpp::InvalidXMLException::error" ref="e0c63b17f7b5b0df20d8361bc9ee92b4" args="" -->
<div class="memitem">
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<table class="memname">
<tr>
<td class="memname">char* <a class="el" href="classneuralpp_1_1InvalidXMLException.html#e0c63b17f7b5b0df20d8361bc9ee92b4">neuralpp::InvalidXMLException::error</a><code> [private]</code> </td>
</tr>
</table>
</div>
<div class="memdoc">
<p>
<p>Referenced by <a class="el" href="neural_09_09__exception_8hpp-source.html#l00051">InvalidXMLException()</a>, and <a class="el" href="neural_09_09__exception_8hpp-source.html#l00056">what()</a>.</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>
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<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>
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@ -345,7 +345,7 @@ It propagates its activation values to the output layers.
<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>
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<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>
</table></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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@ -88,7 +88,7 @@ Exception thrown when doing an attempt to load a network from an invalid file. <
<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>
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<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>
</table></div>
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@ -84,7 +84,7 @@ Exception thrown when trying to write the network's information to a file that c
<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;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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@ -27,7 +27,7 @@
<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>
</table></div>
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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@ -84,7 +84,7 @@ Exception raised when trying to access a neuron whose index is larger than the n
<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;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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<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#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#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#562dfe9fb8d73bf25a23ce608451d3aa">expected</a>() 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#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#51a1851ed07b85bec091c9053ae99cf7">getExpected</a>() 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#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#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>
@ -40,7 +39,8 @@
<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#46f23f462318a4ffc037a4e806364c3f">link</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#a060e28b438613a6cc9e0895ddbc292b">loadFromBinary</a>(const std::string 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#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#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>
@ -48,19 +48,19 @@
<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#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#520147d9b47b69565567bd3fdcfd8897">saveToBinary</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><code> [private]</code></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><code> [private]</code></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#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#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#b0bd1daadb06980dff1f50d33a7c098e">update</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#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#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 Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 2009 for Neural++ by&nbsp;
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View File

@ -53,39 +53,27 @@
<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">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">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="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">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">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="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">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#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="#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#a060e28b438613a6cc9e0895ddbc292b">loadFromBinary</a> (const std::string fname) throw (NetworkFileNotFoundException)</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">DEPRECATED. <a href="#a060e28b438613a6cc9e0895ddbc292b"></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#520147d9b47b69565567bd3fdcfd8897">saveToBinary</a> (const char *fname) throw (NetworkFileWriteException)</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">DEPRECATED. <a href="#520147d9b47b69565567bd3fdcfd8897"></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#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="#1c9e17437d41a7048611e21a3cc1c7dd"></a><br></td></tr>
@ -93,9 +81,6 @@
<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="#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="#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="#0a2733037af912b3e6a10146e7b7172f"></a><br></td></tr>
@ -113,12 +98,27 @@
<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#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="#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 squared deviance. <a href="#8a140d28e6dd4097470c7c138801ad01"></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">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">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#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 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>
@ -140,7 +140,7 @@ Main project's class.
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="el" href="examples_2adderFromString_8cpp-example.html#_a0">examples/adderFromString.cpp</a>, <a class="el" href="examples_2doAdd_8cpp-example.html#_a0">examples/doAdd.cpp</a>, <a class="el" href="examples_2learnAdd_8cpp-example.html#_a0">examples/learnAdd.cpp</a>, and <a class="el" href="examples_2networkForSumsAndSubtractions_8cpp-example.html#_a0">examples/networkForSumsAndSubtractions.cpp</a>.</dl><hr><h2>Member Enumeration Documentation</h2>
<a class="anchor" name="94c36c94060e785ea67a0014c4182f8f"></a><!-- doxytag: member="neuralpp::NeuralNet::source" ref="94c36c94060e785ea67a0014c4182f8f" args="" -->
<div class="memitem">
<div class="memproto">
@ -312,33 +312,6 @@ Constructor.
It updates the weights of the net's synapsis through back-propagation.
<p>
In-class use only
</div>
</div><p>
<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> &amp;&nbsp;</td>
<td class="paramname"> <em>l</em> </td>
<td>&nbsp;)&nbsp;</td>
<td><code> [private]</code></td>
</tr>
</table>
</div>
<div class="memdoc">
<p>
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.
<p>
In-class use only <dl compact><dt><b>Parameters:</b></dt><dd>
<table border="0" cellspacing="2" cellpadding="0">
<tr><td valign="top"></td><td valign="top"><em>l</em>&nbsp;</td><td><a class="el" href="classneuralpp_1_1Layer.html" title="Class for managing layers of neurons.">Layer</a> to commit the changes </td></tr>
</table>
</dl>
</div>
</div><p>
<a class="anchor" name="8a140d28e6dd4097470c7c138801ad01"></a><!-- doxytag: member="neuralpp::NeuralNet::error" ref="8a140d28e6dd4097470c7c138801ad01" args="(double ex)" -->
@ -367,74 +340,6 @@ Get the error made on the expected result as squared deviance.
</dl>
<dl class="return" compact><dt><b>Returns:</b></dt><dd>Mean error </dd></dl>
</div>
</div><p>
<a class="anchor" name="961dce8913264bf64c899dce4e25f810"></a><!-- doxytag: member="neuralpp::NeuralNet::getOutput" ref="961dce8913264bf64c899dce4e25f810" args="() const " -->
<div class="memitem">
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<td class="memname">double neuralpp::NeuralNet::getOutput </td>
<td>(</td>
<td class="paramname"> </td>
<td>&nbsp;)&nbsp;</td>
<td> const</td>
</tr>
</table>
</div>
<div class="memdoc">
<p>
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="e08cdcf4b70f987700e553d9914f6179"></a><!-- doxytag: member="neuralpp::NeuralNet::getThreshold" ref="e08cdcf4b70f987700e553d9914f6179" args="() const " -->
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<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>
<td></td>
</tr>
</table>
</div>
<div class="memdoc">
<p>
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 " -->
@ -446,7 +351,7 @@ It gets the output of the network in case the output layer contains more neurons
<td>(</td>
<td class="paramname"> </td>
<td>&nbsp;)&nbsp;</td>
<td> const</td>
<td> const<code> [private]</code></td>
</tr>
</table>
</div>
@ -468,7 +373,7 @@ Of course you should specify this when you build your network by using setExpect
<td>(</td>
<td class="paramname"> </td>
<td>&nbsp;)&nbsp;</td>
<td> const</td>
<td> const<code> [private]</code></td>
</tr>
</table>
</div>
@ -491,7 +396,7 @@ Of course you should specify this when you build your network by using setExpect
<td class="paramtype">double&nbsp;</td>
<td class="paramname"> <em>ex</em> </td>
<td>&nbsp;)&nbsp;</td>
<td></td>
<td><code> [private]</code></td>
</tr>
</table>
</div>
@ -518,7 +423,7 @@ It sets the value you expect from your network (in case the network has an only
<td class="paramtype">std::vector&lt; double &gt;&nbsp;</td>
<td class="paramname"> <em>ex</em> </td>
<td>&nbsp;)&nbsp;</td>
<td></td>
<td><code> [private]</code></td>
</tr>
</table>
</div>
@ -544,7 +449,7 @@ Set the values you expect from your network.
<td>(</td>
<td class="paramname"> </td>
<td>&nbsp;)&nbsp;</td>
<td></td>
<td><code> [private]</code></td>
</tr>
</table>
</div>
@ -554,6 +459,95 @@ Set the values you expect from your network.
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.
<p>
</div>
</div><p>
<a class="anchor" name="46f23f462318a4ffc037a4e806364c3f"></a><!-- doxytag: member="neuralpp::NeuralNet::link" ref="46f23f462318a4ffc037a4e806364c3f" args="()" -->
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<td class="memname">void neuralpp::NeuralNet::link </td>
<td>(</td>
<td class="paramname"> </td>
<td>&nbsp;)&nbsp;</td>
<td><code> [private]</code></td>
</tr>
</table>
</div>
<div class="memdoc">
<p>
It links the layers of the network (input, hidden, output).
<p>
</div>
</div><p>
<a class="anchor" name="961dce8913264bf64c899dce4e25f810"></a><!-- doxytag: member="neuralpp::NeuralNet::getOutput" ref="961dce8913264bf64c899dce4e25f810" args="() const " -->
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<td class="memname">double neuralpp::NeuralNet::getOutput </td>
<td>(</td>
<td class="paramname"> </td>
<td>&nbsp;)&nbsp;</td>
<td> const</td>
</tr>
</table>
</div>
<div class="memdoc">
<p>
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_2adderFromString_8cpp-example.html#a4">examples/adderFromString.cpp</a>, and <a class="el" href="examples_2doAdd_8cpp-example.html#a5">examples/doAdd.cpp</a>.</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>
<td></td>
</tr>
</table>
</div>
<div class="memdoc">
<p>
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_2networkForSumsAndSubtractions_8cpp-example.html#a4">examples/networkForSumsAndSubtractions.cpp</a>.</dl>
</div>
</div><p>
<a class="anchor" name="e08cdcf4b70f987700e553d9914f6179"></a><!-- doxytag: member="neuralpp::NeuralNet::getThreshold" ref="e08cdcf4b70f987700e553d9914f6179" args="() const " -->
<div class="memitem">
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<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="c129c180647362da963758bfd1ba6890"></a><!-- doxytag: member="neuralpp::NeuralNet::propagate" ref="c129c180647362da963758bfd1ba6890" args="()" -->
@ -575,7 +569,7 @@ It updates through back-propagation the weights of the synapsis and computes aga
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 <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>
<a class="el" href="examples_2adderFromString_8cpp-example.html#a3">examples/adderFromString.cpp</a>, <a class="el" href="examples_2doAdd_8cpp-example.html#a4">examples/doAdd.cpp</a>, and <a class="el" href="examples_2networkForSumsAndSubtractions_8cpp-example.html#a3">examples/networkForSumsAndSubtractions.cpp</a>.</dl>
</div>
</div><p>
<a class="anchor" name="405b32d2928344314ecf0469070b0f17"></a><!-- doxytag: member="neuralpp::NeuralNet::setInput" ref="405b32d2928344314ecf0469070b0f17" args="(std::vector&lt; double &gt; v)" -->
@ -603,28 +597,7 @@ It sets the input for the network.
</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="()" -->
<div class="memitem">
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<td class="memname">void neuralpp::NeuralNet::link </td>
<td>(</td>
<td class="paramname"> </td>
<td>&nbsp;)&nbsp;</td>
<td></td>
</tr>
</table>
</div>
<div class="memdoc">
<p>
It links the layers of the network (input, hidden, output).
<p>
Don't use unless you exactly know what you're doing, it is already called by the constructor
<a class="el" href="examples_2adderFromString_8cpp-example.html#a2">examples/adderFromString.cpp</a>, <a class="el" href="examples_2doAdd_8cpp-example.html#a3">examples/doAdd.cpp</a>, and <a class="el" href="examples_2networkForSumsAndSubtractions_8cpp-example.html#a2">examples/networkForSumsAndSubtractions.cpp</a>.</dl>
</div>
</div><p>
<a class="anchor" name="fdf94c276720c25e565cac834fe8a407"></a><!-- doxytag: member="neuralpp::NeuralNet::save" ref="fdf94c276720c25e565cac834fe8a407" args="(const char *fname)" -->
@ -658,6 +631,70 @@ Save a trained neural network to a binary file.
</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="a060e28b438613a6cc9e0895ddbc292b"></a><!-- doxytag: member="neuralpp::NeuralNet::loadFromBinary" ref="a060e28b438613a6cc9e0895ddbc292b" args="(const std::string fname)" -->
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<td class="memname">void neuralpp::NeuralNet::loadFromBinary </td>
<td>(</td>
<td class="paramtype">const std::string&nbsp;</td>
<td class="paramname"> <em>fname</em> </td>
<td>&nbsp;)&nbsp;</td>
<td> throw (<a class="el" href="classneuralpp_1_1NetworkFileNotFoundException.html">NetworkFileNotFoundException</a>)</td>
</tr>
</table>
</div>
<div class="memdoc">
<p>
DEPRECATED.
<p>
Load a trained neural network from a binary file. This function is deprecated and kept for back-compatibility. Use the XML format instead to load and neural networks and, respectly, the NeuralNetwork(const std::string) constructor or the <a class="el" href="classneuralpp_1_1NeuralNet.html#fdf94c276720c25e565cac834fe8a407" title="Save a trained neural network to a binary file.">save(const char*)</a> methods. <dl compact><dt><b>Parameters:</b></dt><dd>
<table border="0" cellspacing="2" cellpadding="0">
<tr><td valign="top"></td><td valign="top"><em>fname</em>&nbsp;</td><td>Name of the file to be loaded </td></tr>
</table>
</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><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>When you're trying to load an invalid network file </td></tr>
</table>
</dl>
</div>
</div><p>
<a class="anchor" name="520147d9b47b69565567bd3fdcfd8897"></a><!-- doxytag: member="neuralpp::NeuralNet::saveToBinary" ref="520147d9b47b69565567bd3fdcfd8897" args="(const char *fname)" -->
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<td class="memname">void neuralpp::NeuralNet::saveToBinary </td>
<td>(</td>
<td class="paramtype">const char *&nbsp;</td>
<td class="paramname"> <em>fname</em> </td>
<td>&nbsp;)&nbsp;</td>
<td> throw (<a class="el" href="classneuralpp_1_1NetworkFileWriteException.html">NetworkFileWriteException</a>)</td>
</tr>
</table>
</div>
<div class="memdoc">
<p>
DEPRECATED.
<p>
Save a trained neural network to a binary file. This function is deprecated and kept for back-compatibility. Use the XML format instead to load and neural networks and, respectly, the NeuralNetwork(const std::string) constructor or the <a class="el" href="classneuralpp_1_1NeuralNet.html#fdf94c276720c25e565cac834fe8a407" title="Save a trained neural network to a binary file.">save(const char*)</a> methods. <dl compact><dt><b>Parameters:</b></dt><dd>
<table border="0" cellspacing="2" cellpadding="0">
<tr><td valign="top"></td><td valign="top"><em>fname</em>&nbsp;</td><td>Name of the file to be saved with the network information </td></tr>
</table>
</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><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 try to write the network information to an invalid file </td></tr>
</table>
</dl>
</div>
</div><p>
<a class="anchor" name="1c9e17437d41a7048611e21a3cc1c7dd"></a><!-- doxytag: member="neuralpp::NeuralNet::train" ref="1c9e17437d41a7048611e21a3cc1c7dd" args="(std::string xml, source src)" -->
@ -700,7 +737,7 @@ A sample XML file is available in examples/adder.xml <dl compact><dt><b>Paramete
</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>
<a class="el" href="examples_2adderFromString_8cpp-example.html#a1">examples/adderFromString.cpp</a>, <a class="el" href="examples_2learnAdd_8cpp-example.html#a1">examples/learnAdd.cpp</a>, and <a class="el" href="examples_2networkForSumsAndSubtractions_8cpp-example.html#a1">examples/networkForSumsAndSubtractions.cpp</a>.</dl>
</div>
</div><p>
<a class="anchor" name="96da6712a72051cf34ad961761ef6e08"></a><!-- doxytag: member="neuralpp::NeuralNet::initXML" ref="96da6712a72051cf34ad961761ef6e08" args="(std::string &amp;xml)" -->
@ -728,44 +765,6 @@ Initialize the training XML for the neural network.
</table>
</dl>
</div>
</div><p>
<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 std::vector&lt;double&gt; neuralpp::NeuralNet::split </td>
<td>(</td>
<td class="paramtype">char&nbsp;</td>
<td class="paramname"> <em>delim</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">std::string&nbsp;</td>
<td class="paramname"> <em>str</em></td><td>&nbsp;</td>
</tr>
<tr>
<td></td>
<td>)</td>
<td></td><td></td><td><code> [static]</code></td>
</tr>
</table>
</div>
<div class="memdoc">
<p>
Splits a string into a vector of doubles, given a delimitator.
<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>delim</em>&nbsp;</td><td>Delimitator </td></tr>
<tr><td valign="top"></td><td valign="top"><em>str</em>&nbsp;</td><td>String to be splitted </td></tr>
</table>
</dl>
<dl class="return" compact><dt><b>Returns:</b></dt><dd>Vector of doubles containing splitted values </dd></dl>
</div>
</div><p>
<a class="anchor" name="0a2733037af912b3e6a10146e7b7172f"></a><!-- doxytag: member="neuralpp::NeuralNet::XMLFromSet" ref="0a2733037af912b3e6a10146e7b7172f" args="(int &amp;id, std::string set)" -->
@ -974,7 +973,7 @@ 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 Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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@ -40,12 +40,14 @@
<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#6fa3e8afc1c6e6e427773ba89a6fcb68">setSynIn</a>(size_t n)</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#d6ae3a93ecd11c345d931aee4ca248c1">setSynOut</a>(size_t n)</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 Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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@ -59,6 +59,10 @@
<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#aa6e58f073a76b3481fea9115a4e6ea6">setProp</a> (double p)</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Change the propagation value of the neuron. <a href="#aa6e58f073a76b3481fea9115a4e6ea6"></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#6fa3e8afc1c6e6e427773ba89a6fcb68">setSynIn</a> (size_t n)</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#d6ae3a93ecd11c345d931aee4ca248c1">setSynOut</a> (size_t n)</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#55993867179f0ac7d1e0e2c460ceb611">getActv</a> ()</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Get the activation value of the neuron. <a href="#55993867179f0ac7d1e0e2c460ceb611"></a><br></td></tr>
@ -346,6 +350,46 @@ Change the propagation value of the neuron.
</table>
</dl>
</div>
</div><p>
<a class="anchor" name="6fa3e8afc1c6e6e427773ba89a6fcb68"></a><!-- doxytag: member="neuralpp::Neuron::setSynIn" ref="6fa3e8afc1c6e6e427773ba89a6fcb68" args="(size_t n)" -->
<div class="memitem">
<div class="memproto">
<table class="memname">
<tr>
<td class="memname">void neuralpp::Neuron::setSynIn </td>
<td>(</td>
<td class="paramtype">size_t&nbsp;</td>
<td class="paramname"> <em>n</em> </td>
<td>&nbsp;)&nbsp;</td>
<td></td>
</tr>
</table>
</div>
<div class="memdoc">
<p>
</div>
</div><p>
<a class="anchor" name="d6ae3a93ecd11c345d931aee4ca248c1"></a><!-- doxytag: member="neuralpp::Neuron::setSynOut" ref="d6ae3a93ecd11c345d931aee4ca248c1" args="(size_t n)" -->
<div class="memitem">
<div class="memproto">
<table class="memname">
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<td class="memname">void neuralpp::Neuron::setSynOut </td>
<td>(</td>
<td class="paramtype">size_t&nbsp;</td>
<td class="paramname"> <em>n</em> </td>
<td>&nbsp;)&nbsp;</td>
<td></td>
</tr>
</table>
</div>
<div class="memdoc">
<p>
</div>
</div><p>
<a class="anchor" name="55993867179f0ac7d1e0e2c460ceb611"></a><!-- doxytag: member="neuralpp::Neuron::getActv" ref="55993867179f0ac7d1e0e2c460ceb611" args="()" -->
@ -572,7 +616,7 @@ 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 Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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@ -37,12 +37,12 @@
<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>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1Synapsis.html#acee77d0fdf9889464ab5ed27beae0ff">setWeight</a>(double w)</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#0729de9e737b9967421edcfc4b410bd8">Synapsis</a>(Neuron *i, Neuron *o, double w, double d)</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#c7760b19c56e9f69994970311703c5fa">Synapsis</a>()</td><td><a class="el" href="classneuralpp_1_1Synapsis.html">neuralpp::Synapsis</a></td><td><code> [inline]</code></td></tr>
<tr class="memlist"><td><a class="el" href="classneuralpp_1_1Synapsis.html#b767332fdce81af25486b8969e5d2fb3">Synapsis</a>(Neuron *i, Neuron *o, 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#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 Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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@ -35,9 +35,9 @@
<a href="classneuralpp_1_1Synapsis-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_1Synapsis.html#0729de9e737b9967421edcfc4b410bd8">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 d)</td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classneuralpp_1_1Synapsis.html#c7760b19c56e9f69994970311703c5fa">Synapsis</a> ()</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Constructor. <a href="#0729de9e737b9967421edcfc4b410bd8"></a><br></td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Empty constructor (it does nothing). <a href="#c7760b19c56e9f69994970311703c5fa"></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_1Synapsis.html#b767332fdce81af25486b8969e5d2fb3">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(*a)(double))</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Constructor. <a href="#b767332fdce81af25486b8969e5d2fb3"></a><br></td></tr>
@ -84,54 +84,24 @@
Class for managing synapsis.
<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="0729de9e737b9967421edcfc4b410bd8"></a><!-- doxytag: member="neuralpp::Synapsis::Synapsis" ref="0729de9e737b9967421edcfc4b410bd8" args="(Neuron *i, Neuron *o, double w, double d)" -->
<a class="anchor" name="c7760b19c56e9f69994970311703c5fa"></a><!-- doxytag: member="neuralpp::Synapsis::Synapsis" ref="c7760b19c56e9f69994970311703c5fa" args="()" -->
<div class="memitem">
<div class="memproto">
<table class="memname">
<tr>
<td class="memname">neuralpp::Synapsis::Synapsis </td>
<td>(</td>
<td class="paramtype"><a class="el" href="classneuralpp_1_1Neuron.html">Neuron</a> *&nbsp;</td>
<td class="paramname"> <em>i</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype"><a class="el" href="classneuralpp_1_1Neuron.html">Neuron</a> *&nbsp;</td>
<td class="paramname"> <em>o</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">double&nbsp;</td>
<td class="paramname"> <em>w</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">double&nbsp;</td>
<td class="paramname"> <em>d</em></td><td>&nbsp;</td>
</tr>
<tr>
<td></td>
<td>)</td>
<td></td><td></td><td></td>
<td class="paramname"> </td>
<td>&nbsp;)&nbsp;</td>
<td><code> [inline]</code></td>
</tr>
</table>
</div>
<div class="memdoc">
<p>
Constructor.
Empty constructor (it does nothing).
<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>i</em>&nbsp;</td><td>Input neuron </td></tr>
<tr><td valign="top"></td><td valign="top"><em>o</em>&nbsp;</td><td>Output neuron </td></tr>
<tr><td valign="top"></td><td valign="top"><em>w</em>&nbsp;</td><td>Weight for the synapsis </td></tr>
<tr><td valign="top"></td><td valign="top"><em>d</em>&nbsp;</td><td>Delta for the synapsis </td></tr>
</table>
</dl>
</div>
</div><p>
@ -523,7 +493,7 @@ 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>
</div>
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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@ -18,12 +18,13 @@
</div>
<div class="contents">
<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_2adderFromString_8cpp-example.html">examples/adderFromString.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>
<li><a class="el" href="examples_2networkForSumsAndSubtractions_8cpp-example.html">examples/networkForSumsAndSubtractions.cpp</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;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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@ -59,7 +59,7 @@
}
</pre></div> </div>
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Thu Sep 3 17:01:39 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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@ -0,0 +1,67 @@
<!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/adderFromString.cpp</title>
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<!-- Generated by Doxygen 1.5.6 -->
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<div class="contents">
<h1>examples/adderFromString.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, 1, 0.002, 1000);
<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"</span>);
xml += NeuralNet::XMLFromSet(<span class="keywordtype">id</span>, <span class="stringliteral">"6,3;9"</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">"4,4;8"</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#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;
}
</pre></div> </div>
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 2009 for Neural++ by&nbsp;
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@ -25,7 +25,7 @@
<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">#define NETFILE "network.xml"</span>
<span class="preprocessor"></span>
<span class="keywordtype">int</span> main() {
<span class="keywordtype">double</span> a,b;
@ -61,7 +61,7 @@
}
</pre></div> </div>
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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@ -36,10 +36,10 @@
<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; a learning rate == 0.002 (just get it doing some tests until satisfied, but remember to keep its value quite low and ~ 0 to keep the network stable)</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);
<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, 0.002, 2000);
<span class="comment">// Initialize a training XML as a string in 'xml'</span>
NeuralNet::initXML(xml);
@ -56,6 +56,12 @@
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>);
xml += NeuralNet::XMLFromSet(<span class="keywordtype">id</span>, <span class="stringliteral">"4,1;5"</span>);
xml += NeuralNet::XMLFromSet(<span class="keywordtype">id</span>, <span class="stringliteral">"2,6;8"</span>);
xml += NeuralNet::XMLFromSet(<span class="keywordtype">id</span>, <span class="stringliteral">"2,7;9"</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">"4,7;11"</span>);
xml += NeuralNet::XMLFromSet(<span class="keywordtype">id</span>, <span class="stringliteral">"5,2;7"</span>);
NeuralNet::closeXML(xml);
<span class="comment">// Save the XML string just created to a file</span>
@ -72,13 +78,13 @@
<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>);
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">"network.xml"</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;
}
</pre></div> </div>
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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@ -0,0 +1,66 @@
<!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/networkForSumsAndSubtractions.cpp</title>
<link href="doxygen.css" rel="stylesheet" type="text/css">
<link href="tabs.css" rel="stylesheet" type="text/css">
</head><body>
<!-- Generated by Doxygen 1.5.6 -->
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<div class="tabs">
<ul>
<li><a href="index.html"><span>Main&nbsp;Page</span></a></li>
<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>examples/networkForSumsAndSubtractions.cpp</h1>This program creates a neural network from scratch. Its purpose is to get two numbers and learn to compute their sum and difference (so the network provides two output values). The training set is auto-generated to an XML string, and then the network is trained.<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, 0.002, 1000);
<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 3+2=5, 3-2=1; 4+2=6, 4-2=2; 6+3=9, 6-3=3</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: "</span>;
cin &gt;&gt; tmp;
v.push_back(tmp);
cout &lt;&lt; <span class="stringliteral">"Second number: "</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;
}
</pre></div> </div>
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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>
</html>

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@ -0,0 +1,26 @@
<!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/networkForSumsAndSubtrations.cpp</title>
<link href="doxygen.css" rel="stylesheet" type="text/css">
<link href="tabs.css" rel="stylesheet" type="text/css">
</head><body>
<!-- Generated by Doxygen 1.5.6 -->
<div class="navigation" id="top">
<div class="tabs">
<ul>
<li><a href="index.html"><span>Main&nbsp;Page</span></a></li>
<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>examples/networkForSumsAndSubtrations.cpp</h1>This program creates a neural network from scratch. Its purpose is to get two numbers and learn to compute their sum and difference (so the network provides two output values). The training set is auto-generated to an XML string, and then the network is trained.<p>
<div class="fragment"><pre class="fragment"></pre></div> </div>
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:24:50 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>
</html>

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@ -29,7 +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>
</table>
</div>
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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

@ -94,7 +94,7 @@ Here is a list of all class members with links to the classes they belong to:
: <a class="el" href="classCMarkup.html#3257cd5f249587254e816d12bd3b0e0d">CMarkup</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;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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@ -68,8 +68,6 @@ Here is a list of all class members with links to the classes they belong to:
: <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#f697a8d9967ad8f03e5a16a42cd110c5">neuralpp::NeuralNet</a>
<li>ContentLen()
: <a class="el" href="structCMarkup_1_1ElemPos.html#9099635ab9239103aa930b2f1a456d2d">CMarkup::ElemPos</a>
<li>ConvertEncoding()
@ -78,7 +76,7 @@ Here is a list of all class members with links to the classes they belong to:
: <a class="el" href="structCMarkup_1_1NodeStack.html#499a05e053b785df518fb0b6124fd0ee">CMarkup::NodeStack</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;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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@ -71,7 +71,7 @@ Here is a list of all class members with links to the classes they belong to:
: <a class="el" href="classCMarkup.html#f91e20dfe9e95194e3ca8143eeb889c2">CMarkup</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;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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@ -72,8 +72,9 @@ Here is a list of all class members with links to the classes they belong to:
<li>epochs
: <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#8a140d28e6dd4097470c7c138801ad01">neuralpp::NeuralNet</a>
<li>error
: <a class="el" href="classneuralpp_1_1InvalidXMLException.html#e0c63b17f7b5b0df20d8361bc9ee92b4">neuralpp::InvalidXMLException</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
@ -84,7 +85,7 @@ Here is a list of all class members with links to the classes they belong to:
: <a class="el" href="classneuralpp_1_1NeuralNet.html#562dfe9fb8d73bf25a23ce608451d3aa">neuralpp::NeuralNet</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;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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@ -73,7 +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>
</div>
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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@ -115,7 +115,7 @@ Here is a list of all class members with links to the classes they belong to:
: <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 Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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@ -65,7 +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 Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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@ -93,7 +93,7 @@ Here is a list of all class members with links to the classes they belong to:
<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>
: <a class="el" href="classneuralpp_1_1InvalidXMLException.html#793d311be88606908abf8c5be1348586">neuralpp::InvalidXMLException</a>
<li>iPos
: <a class="el" href="structCMarkup_1_1SavedPos.html#649563d0d7c11bf2fdebbc0dbe396321">CMarkup::SavedPos</a>
<li>IsEmptyElement()
@ -102,7 +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>
</div>
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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@ -69,13 +69,15 @@ Here is a list of all class members with links to the classes they belong to:
<li>Level()
: <a class="el" href="structCMarkup_1_1ElemPos.html#cdea1fc74ed96d413138c6c2d9b0a4f7">CMarkup::ElemPos</a>
<li>link()
: <a class="el" href="classneuralpp_1_1Layer.html#ac33444fde14633fa1ad4acb024ad150">neuralpp::Layer</a>
, <a class="el" href="classneuralpp_1_1NeuralNet.html#46f23f462318a4ffc037a4e806364c3f">neuralpp::NeuralNet</a>
: <a class="el" href="classneuralpp_1_1NeuralNet.html#46f23f462318a4ffc037a4e806364c3f">neuralpp::NeuralNet</a>
, <a class="el" href="classneuralpp_1_1Layer.html#ac33444fde14633fa1ad4acb024ad150">neuralpp::Layer</a>
<li>Load()
: <a class="el" href="classCMarkup.html#c7604e24564eac2dce702f7fbaf430a6">CMarkup</a>
<li>loadFromBinary()
: <a class="el" href="classneuralpp_1_1NeuralNet.html#a060e28b438613a6cc9e0895ddbc292b">neuralpp::NeuralNet</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;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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@ -171,7 +171,7 @@ Here is a list of all class members with links to the classes they belong to:
: <a class="el" href="classneuralpp_1_1Synapsis.html#cff10a022d4c021688e4df944c05d8bd">neuralpp::Synapsis</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;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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@ -134,7 +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>
</div>
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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@ -77,7 +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>
</div>
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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@ -95,7 +95,7 @@ Here is a list of all class members with links to the classes they belong to:
: <a class="el" href="classneuralpp_1_1Neuron.html#2c0acb0e6d413c4e0fc9e7939da1a684">neuralpp::Neuron</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;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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@ -86,7 +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>
</div>
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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@ -59,10 +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="classneuralpp_1_1NeuralNet.html#fdf94c276720c25e565cac834fe8a407">neuralpp::NeuralNet</a>
<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>SavedPos()
: <a class="el" href="structCMarkup_1_1SavedPos.html#203b3a22eb86b1131985a6631e3d3c47">CMarkup::SavedPos</a>
<li>SavedPosMap()
@ -71,6 +71,8 @@ Here is a list of all class members with links to the classes they belong to:
: <a class="el" href="structCMarkup_1_1SavedPosMapArray.html#0fca988b3417d41ccf3e2b3e8fef7483">CMarkup::SavedPosMapArray</a>
<li>SavePos()
: <a class="el" href="classCMarkup.html#21279989fdcfbed6ed4d8824b9614eb0">CMarkup</a>
<li>saveToBinary()
: <a class="el" href="classneuralpp_1_1NeuralNet.html#520147d9b47b69565567bd3fdcfd8897">neuralpp::NeuralNet</a>
<li>SegsUsed()
: <a class="el" href="structCMarkup_1_1PosArray.html#0310976aa8e777cb84ab02ddbae8864c">CMarkup::PosArray</a>
<li>setActv()
@ -82,7 +84,7 @@ 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#ce922c959d826b28f4ad2b279697238b">CMarkup</a>
: <a class="el" href="classCMarkup.html#65f994e7c180c9e02cb8a3deb9cc1a32">CMarkup</a>
<li>setDelta()
: <a class="el" href="classneuralpp_1_1Synapsis.html#429ad5b25930faf436a9d725582802e1">neuralpp::Synapsis</a>
<li>SetDoc()
@ -106,14 +108,16 @@ Here is a list of all class members with links to the classes they belong to:
: <a class="el" href="classneuralpp_1_1Neuron.html#aa6e58f073a76b3481fea9115a4e6ea6">neuralpp::Neuron</a>
<li>SetStartTagLen()
: <a class="el" href="structCMarkup_1_1ElemPos.html#6f366b2f636e221db004bf44fd952912">CMarkup::ElemPos</a>
<li>setSynIn()
: <a class="el" href="classneuralpp_1_1Neuron.html#6fa3e8afc1c6e6e427773ba89a6fcb68">neuralpp::Neuron</a>
<li>setSynOut()
: <a class="el" href="classneuralpp_1_1Neuron.html#d6ae3a93ecd11c345d931aee4ca248c1">neuralpp::Neuron</a>
<li>setWeight()
: <a class="el" href="classneuralpp_1_1Synapsis.html#acee77d0fdf9889464ab5ed27beae0ff">neuralpp::Synapsis</a>
<li>size()
: <a class="el" href="classneuralpp_1_1Layer.html#7ca71ed62fbe9c1e9c0fb6a8dcaf76f0">neuralpp::Layer</a>
<li>source
: <a class="el" href="classneuralpp_1_1NeuralNet.html#94c36c94060e785ea67a0014c4182f8f">neuralpp::NeuralNet</a>
<li>split()
: <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 +149,7 @@ 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#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()
@ -154,7 +158,7 @@ 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>
</ul>
</div>
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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@ -73,7 +73,7 @@ Here is a list of all class members with links to the classes they belong to:
: <a class="el" href="classneuralpp_1_1NeuralNet.html#1c9e17437d41a7048611e21a3cc1c7dd">neuralpp::NeuralNet</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;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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@ -75,7 +75,7 @@ Here is a list of all class members with links to the classes they belong to:
: <a class="el" href="classCMarkup.html#8e6cb088e69b6078f5923b0940fd647c">CMarkup</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;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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@ -73,7 +73,7 @@ Here is a list of all class members with links to the classes they belong to:
: <a class="el" href="classCMarkup.html#983286cbcb7c4f9aa1f462ffb5dc641f">CMarkup</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;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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@ -165,7 +165,7 @@ Here is a list of all class members with links to the classes they belong to:
: <a class="el" href="classneuralpp_1_1NeuralNet.html#0a2733037af912b3e6a10146e7b7172f">neuralpp::NeuralNet</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;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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@ -71,7 +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>
</ul>
</div>
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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@ -47,7 +47,7 @@
: <a class="el" href="classneuralpp_1_1NeuralNet.html#94c36c94060e785ea67a0014c4182f8f">neuralpp::NeuralNet</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;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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@ -137,7 +137,7 @@
: <a class="el" href="classneuralpp_1_1NeuralNet.html#94c36c94060e785ea67a0014c4182f8f6d06b4fe9414a158c97aee1a3679a904">neuralpp::NeuralNet</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;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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@ -84,7 +84,7 @@
: <a class="el" href="classCMarkup.html#3257cd5f249587254e816d12bd3b0e0d">CMarkup</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;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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@ -67,8 +67,6 @@
: <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#f697a8d9967ad8f03e5a16a42cd110c5">neuralpp::NeuralNet</a>
<li>ContentLen()
: <a class="el" href="structCMarkup_1_1ElemPos.html#9099635ab9239103aa930b2f1a456d2d">CMarkup::ElemPos</a>
<li>ConvertEncoding()
@ -77,7 +75,7 @@
: <a class="el" href="structCMarkup_1_1NodeStack.html#499a05e053b785df518fb0b6124fd0ee">CMarkup::NodeStack</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;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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@ -66,7 +66,7 @@
: <a class="el" href="classCMarkup.html#f91e20dfe9e95194e3ca8143eeb889c2">CMarkup</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;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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@ -74,7 +74,7 @@
: <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 Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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@ -68,7 +68,7 @@
: <a class="el" href="classCMarkup.html#e29573627f9b0cdc0d7152ff749ba407">CMarkup</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;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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@ -114,7 +114,7 @@
: <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 Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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@ -77,14 +77,14 @@
<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>
: <a class="el" href="classneuralpp_1_1InvalidXMLException.html#793d311be88606908abf8c5be1348586">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 Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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@ -69,9 +69,11 @@
, <a class="el" href="classneuralpp_1_1Layer.html#ac33444fde14633fa1ad4acb024ad150">neuralpp::Layer</a>
<li>Load()
: <a class="el" href="classCMarkup.html#c7604e24564eac2dce702f7fbaf430a6">CMarkup</a>
<li>loadFromBinary()
: <a class="el" href="classneuralpp_1_1NeuralNet.html#a060e28b438613a6cc9e0895ddbc292b">neuralpp::NeuralNet</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;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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@ -66,7 +66,7 @@
: <a class="el" href="classneuralpp_1_1Synapsis.html#cff10a022d4c021688e4df944c05d8bd">neuralpp::Synapsis</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;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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@ -78,7 +78,7 @@
: <a class="el" href="classneuralpp_1_1Neuron.html#fe458021e3b20d58dc608fb94ae2135b">neuralpp::Neuron</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;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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@ -69,7 +69,7 @@
: <a class="el" href="classCMarkup.html#012bca9ceaf157033a5697fa6ea92e45">CMarkup</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;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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@ -70,7 +70,7 @@
: <a class="el" href="classneuralpp_1_1Neuron.html#2c0acb0e6d413c4e0fc9e7939da1a684">neuralpp::Neuron</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;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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@ -83,7 +83,7 @@
: <a class="el" href="classCMarkup.html#dbab6d52d320eac695850f0b47e5b5ce">CMarkup</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;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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@ -58,10 +58,10 @@
&nbsp;
<p>
<h3><a class="anchor" name="index_s">- s -</a></h3><ul>
<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>save()
: <a class="el" href="classneuralpp_1_1NeuralNet.html#fdf94c276720c25e565cac834fe8a407">neuralpp::NeuralNet</a>
<li>SavedPos()
: <a class="el" href="structCMarkup_1_1SavedPos.html#203b3a22eb86b1131985a6631e3d3c47">CMarkup::SavedPos</a>
<li>SavedPosMap()
@ -70,6 +70,8 @@
: <a class="el" href="structCMarkup_1_1SavedPosMapArray.html#0fca988b3417d41ccf3e2b3e8fef7483">CMarkup::SavedPosMapArray</a>
<li>SavePos()
: <a class="el" href="classCMarkup.html#21279989fdcfbed6ed4d8824b9614eb0">CMarkup</a>
<li>saveToBinary()
: <a class="el" href="classneuralpp_1_1NeuralNet.html#520147d9b47b69565567bd3fdcfd8897">neuralpp::NeuralNet</a>
<li>SegsUsed()
: <a class="el" href="structCMarkup_1_1PosArray.html#0310976aa8e777cb84ab02ddbae8864c">CMarkup::PosArray</a>
<li>setActv()
@ -81,7 +83,7 @@
<li>SetChildData()
: <a class="el" href="classCMarkup.html#b2db581de961cbdf0004e9377029a8c7">CMarkup</a>
<li>SetData()
: <a class="el" href="classCMarkup.html#ce922c959d826b28f4ad2b279697238b">CMarkup</a>
: <a class="el" href="classCMarkup.html#65f994e7c180c9e02cb8a3deb9cc1a32">CMarkup</a>
<li>setDelta()
: <a class="el" href="classneuralpp_1_1Synapsis.html#429ad5b25930faf436a9d725582802e1">neuralpp::Synapsis</a>
<li>SetDoc()
@ -95,8 +97,8 @@
<li>setExpected()
: <a class="el" href="classneuralpp_1_1NeuralNet.html#b6475762b7e9eab086befdc511f7c236">neuralpp::NeuralNet</a>
<li>setInput()
: <a class="el" href="classneuralpp_1_1NeuralNet.html#405b32d2928344314ecf0469070b0f17">neuralpp::NeuralNet</a>
, <a class="el" href="classneuralpp_1_1Layer.html#88ceffc23f02a9dc24d4355767b7cca7">neuralpp::Layer</a>
: <a class="el" href="classneuralpp_1_1Layer.html#88ceffc23f02a9dc24d4355767b7cca7">neuralpp::Layer</a>
, <a class="el" href="classneuralpp_1_1NeuralNet.html#405b32d2928344314ecf0469070b0f17">neuralpp::NeuralNet</a>
<li>SetLevel()
: <a class="el" href="structCMarkup_1_1ElemPos.html#625d84902ebb86bda4d5c5720f00e885">CMarkup::ElemPos</a>
<li>SetMapSize()
@ -105,12 +107,14 @@
: <a class="el" href="classneuralpp_1_1Neuron.html#aa6e58f073a76b3481fea9115a4e6ea6">neuralpp::Neuron</a>
<li>SetStartTagLen()
: <a class="el" href="structCMarkup_1_1ElemPos.html#6f366b2f636e221db004bf44fd952912">CMarkup::ElemPos</a>
<li>setSynIn()
: <a class="el" href="classneuralpp_1_1Neuron.html#6fa3e8afc1c6e6e427773ba89a6fcb68">neuralpp::Neuron</a>
<li>setSynOut()
: <a class="el" href="classneuralpp_1_1Neuron.html#d6ae3a93ecd11c345d931aee4ca248c1">neuralpp::Neuron</a>
<li>setWeight()
: <a class="el" href="classneuralpp_1_1Synapsis.html#acee77d0fdf9889464ab5ed27beae0ff">neuralpp::Synapsis</a>
<li>size()
: <a class="el" href="classneuralpp_1_1Layer.html#7ca71ed62fbe9c1e9c0fb6a8dcaf76f0">neuralpp::Layer</a>
<li>split()
: <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 +124,7 @@
<li>StrNIACmp()
: <a class="el" href="structCMarkup_1_1TokenPos.html#c3a37f7294cd763aed0f37749095d3db">CMarkup::TokenPos</a>
<li>Synapsis()
: <a class="el" href="classneuralpp_1_1Synapsis.html#b767332fdce81af25486b8969e5d2fb3">neuralpp::Synapsis</a>
: <a class="el" href="classneuralpp_1_1Synapsis.html#af6b80ab3203bccd2ee4a36f06537517">neuralpp::Synapsis</a>
<li>synClear()
: <a class="el" href="classneuralpp_1_1Neuron.html#2e2ccb69277fc3d992a3a3f2360ed154">neuralpp::Neuron</a>
<li>synIn()
@ -129,7 +133,7 @@
: <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 Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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@ -68,7 +68,7 @@
: <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 Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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@ -72,7 +72,7 @@
: <a class="el" href="classCMarkup.html#8e6cb088e69b6078f5923b0940fd647c">CMarkup</a>
</ul>
</div>
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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@ -68,7 +68,7 @@
: <a class="el" href="classCMarkup.html#983286cbcb7c4f9aa1f462ffb5dc641f">CMarkup</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;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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@ -164,7 +164,7 @@
: <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 Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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@ -70,7 +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 Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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@ -77,6 +77,8 @@
<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>error
: <a class="el" href="classneuralpp_1_1InvalidXMLException.html#e0c63b17f7b5b0df20d8361bc9ee92b4">neuralpp::InvalidXMLException</a>
<li>ex
: <a class="el" href="structneuralpp_1_1netrecord.html#dcc44fde3f67058d26ef2d5cbd0904e6">neuralpp::netrecord</a>
<li>expect
@ -267,7 +269,7 @@
: <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 Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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@ -146,7 +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 Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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: <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 Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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<h1>Neural++ Documentation</h1>
<p>
<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;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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@ -36,9 +36,17 @@ Here is a list of all namespace members with links to the namespace documentatio
: <a class="el" href="namespaceneuralpp.html#7df3a0de999c7a635f2289749ed4f194">neuralpp</a>
<li>df()
: <a class="el" href="namespaceneuralpp.html#43c8197cc83f65fa9676386579671aec">neuralpp</a>
<li>split()
: <a class="el" href="namespaceneuralpp_1_1neuralutils.html#68719b3d63ca48ed264e1b730a1aaa4a">neuralpp::neuralutils</a>
<li>splitLines()
: <a class="el" href="namespaceneuralpp_1_1neuralutils.html#1d887e4bcc7ef2d50cbeca984767a78b">neuralpp::neuralutils</a>
<li>toLower()
: <a class="el" href="namespaceneuralpp_1_1neuralutils.html#f7932c25bd82b19173d2f3d2e5cef488">neuralpp::neuralutils</a>
<li>toUpper()
: <a class="el" href="namespaceneuralpp_1_1neuralutils.html#265b22d1a6110646b42693b96c21ca8b">neuralpp::neuralutils</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;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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@ -36,9 +36,17 @@
: <a class="el" href="namespaceneuralpp.html#7df3a0de999c7a635f2289749ed4f194">neuralpp</a>
<li>df()
: <a class="el" href="namespaceneuralpp.html#43c8197cc83f65fa9676386579671aec">neuralpp</a>
<li>split()
: <a class="el" href="namespaceneuralpp_1_1neuralutils.html#68719b3d63ca48ed264e1b730a1aaa4a">neuralpp::neuralutils</a>
<li>splitLines()
: <a class="el" href="namespaceneuralpp_1_1neuralutils.html#1d887e4bcc7ef2d50cbeca984767a78b">neuralpp::neuralutils</a>
<li>toLower()
: <a class="el" href="namespaceneuralpp_1_1neuralutils.html#f7932c25bd82b19173d2f3d2e5cef488">neuralpp::neuralutils</a>
<li>toUpper()
: <a class="el" href="namespaceneuralpp_1_1neuralutils.html#265b22d1a6110646b42693b96c21ca8b">neuralpp::neuralutils</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;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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<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>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_1_1neuralutils.html">neuralutils</a></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>
@ -120,7 +123,7 @@ Main namespace for the library. <hr><h2>Function Documentation</h2>
</div>
</div><p>
</div>
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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@ -0,0 +1,172 @@
<!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++: neuralpp::neuralutils Namespace Reference</title>
<link href="doxygen.css" rel="stylesheet" type="text/css">
<link href="tabs.css" rel="stylesheet" type="text/css">
</head><body>
<!-- Generated by Doxygen 1.5.6 -->
<div class="navigation" id="top">
<div class="tabs">
<ul>
<li><a href="index.html"><span>Main&nbsp;Page</span></a></li>
<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">
<ul>
<li><a href="namespaces.html"><span>Namespace List</span></a></li>
<li><a href="namespacemembers.html"><span>Namespace&nbsp;Members</span></a></li>
</ul>
</div>
<div class="navpath"><a class="el" href="namespaceneuralpp.html">neuralpp</a>::<a class="el" href="namespaceneuralpp_1_1neuralutils.html">neuralutils</a>
</div>
</div>
<div class="contents">
<h1>neuralpp::neuralutils Namespace Reference</h1>
<p>
<table border="0" cellpadding="0" cellspacing="0">
<tr><td></td></tr>
<tr><td colspan="2"><br><h2>Functions</h2></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="namespaceneuralpp_1_1neuralutils.html#68719b3d63ca48ed264e1b730a1aaa4a">split</a> (char delim, std::string str)</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Split a string into a vector of doubles, given a delimitator. <a href="#68719b3d63ca48ed264e1b730a1aaa4a"></a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">std::vector&lt; std::string &gt;&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespaceneuralpp_1_1neuralutils.html#1d887e4bcc7ef2d50cbeca984767a78b">splitLines</a> (std::string str)</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Split the lines of a string. <a href="#1d887e4bcc7ef2d50cbeca984767a78b"></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="namespaceneuralpp_1_1neuralutils.html#f7932c25bd82b19173d2f3d2e5cef488">toLower</a> (std::string &amp;str)</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Convert the characters of a string to lower case. <a href="#f7932c25bd82b19173d2f3d2e5cef488"></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="namespaceneuralpp_1_1neuralutils.html#265b22d1a6110646b42693b96c21ca8b">toUpper</a> (std::string &amp;str)</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Convert the characters of a string to upper case. <a href="#265b22d1a6110646b42693b96c21ca8b"></a><br></td></tr>
</table>
<hr><h2>Function Documentation</h2>
<a class="anchor" name="68719b3d63ca48ed264e1b730a1aaa4a"></a><!-- doxytag: member="neuralpp::neuralutils::split" ref="68719b3d63ca48ed264e1b730a1aaa4a" args="(char delim, std::string str)" -->
<div class="memitem">
<div class="memproto">
<table class="memname">
<tr>
<td class="memname">std::vector&lt;double&gt; neuralpp::neuralutils::split </td>
<td>(</td>
<td class="paramtype">char&nbsp;</td>
<td class="paramname"> <em>delim</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">std::string&nbsp;</td>
<td class="paramname"> <em>str</em></td><td>&nbsp;</td>
</tr>
<tr>
<td></td>
<td>)</td>
<td></td><td></td><td></td>
</tr>
</table>
</div>
<div class="memdoc">
<p>
Split a string into a vector of doubles, given a delimitator.
<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>delim</em>&nbsp;</td><td>Delimitator </td></tr>
<tr><td valign="top"></td><td valign="top"><em>str</em>&nbsp;</td><td>String to be splitted </td></tr>
</table>
</dl>
<dl class="return" compact><dt><b>Returns:</b></dt><dd>Vector of doubles containing splitted value </dd></dl>
</div>
</div><p>
<a class="anchor" name="1d887e4bcc7ef2d50cbeca984767a78b"></a><!-- doxytag: member="neuralpp::neuralutils::splitLines" ref="1d887e4bcc7ef2d50cbeca984767a78b" args="(std::string str)" -->
<div class="memitem">
<div class="memproto">
<table class="memname">
<tr>
<td class="memname">std::vector&lt;std::string&gt; neuralpp::neuralutils::splitLines </td>
<td>(</td>
<td class="paramtype">std::string&nbsp;</td>
<td class="paramname"> <em>str</em> </td>
<td>&nbsp;)&nbsp;</td>
<td></td>
</tr>
</table>
</div>
<div class="memdoc">
<p>
Split the lines of a string.
<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>str</em>&nbsp;</td><td>String to be splitted </td></tr>
</table>
</dl>
<dl class="return" compact><dt><b>Returns:</b></dt><dd>An array of strings containing the lines of the original string </dd></dl>
</div>
</div><p>
<a class="anchor" name="f7932c25bd82b19173d2f3d2e5cef488"></a><!-- doxytag: member="neuralpp::neuralutils::toLower" ref="f7932c25bd82b19173d2f3d2e5cef488" args="(std::string &amp;str)" -->
<div class="memitem">
<div class="memproto">
<table class="memname">
<tr>
<td class="memname">void neuralpp::neuralutils::toLower </td>
<td>(</td>
<td class="paramtype">std::string &amp;&nbsp;</td>
<td class="paramname"> <em>str</em> </td>
<td>&nbsp;)&nbsp;</td>
<td></td>
</tr>
</table>
</div>
<div class="memdoc">
<p>
Convert the characters of a string to lower case.
<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>str</em>&nbsp;</td><td>String to be converted </td></tr>
</table>
</dl>
</div>
</div><p>
<a class="anchor" name="265b22d1a6110646b42693b96c21ca8b"></a><!-- doxytag: member="neuralpp::neuralutils::toUpper" ref="265b22d1a6110646b42693b96c21ca8b" args="(std::string &amp;str)" -->
<div class="memitem">
<div class="memproto">
<table class="memname">
<tr>
<td class="memname">void neuralpp::neuralutils::toUpper </td>
<td>(</td>
<td class="paramtype">std::string &amp;&nbsp;</td>
<td class="paramname"> <em>str</em> </td>
<td>&nbsp;)&nbsp;</td>
<td></td>
</tr>
</table>
</div>
<div class="memdoc">
<p>
Convert the characters of a string to upper case.
<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>str</em>&nbsp;</td><td>String to be converted </td></tr>
</table>
</dl>
</div>
</div><p>
</div>
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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>
</html>

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@ -25,9 +25,10 @@
<div class="contents">
<h1>Namespace List</h1>Here is a list of all namespaces with brief descriptions:<table>
<tr><td class="indexkey"><a class="el" href="namespaceneuralpp.html">neuralpp</a></td><td class="indexvalue">Main namespace for the library </td></tr>
<tr><td class="indexkey"><a class="el" href="namespaceneuralpp_1_1neuralutils.html">neuralpp::neuralutils</a></td><td class="indexvalue"></td></tr>
</table>
</div>
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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<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="l00023"></a><a class="code" href="neural_09_09_8hpp.html#839a9222721835f53c5b248241f535f4">00023</a> <span class="preprocessor">#define RAND (double) ( (rand() / 10.0) / ((double) RAND_MAX) )</span>
<a name="l00024"></a><a class="code" href="neural_09_09_8hpp.html#05e2bb5b9fc32f0b6b4d84fe43177d72">00024</a> <span class="preprocessor"></span><span class="preprocessor">#define BETA0 0.8</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="l00030"></a>00030 <span class="keyword">namespace </span>neuralpp {
<a name="l00031"></a>00031 <span class="keyword">class </span>Synapsis;
<a name="l00032"></a>00032 <span class="keyword">class </span>Neuron;
<a name="l00033"></a>00033 <span class="keyword">class </span>Layer;
<a name="l00034"></a>00034 <span class="keyword">class </span>NeuralNet;
<a name="l00035"></a>00035
<a name="l00036"></a>00036 <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="l00037"></a>00037 <span class="keywordtype">double</span> <a class="code" href="namespaceneuralpp.html#7df3a0de999c7a635f2289749ed4f194">__actv</a>(<span class="keywordtype">double</span> prop);
<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="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="l00067"></a><a class="code" href="classneuralpp_1_1NeuralNet.html">00067</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="l00068"></a><a class="code" href="classneuralpp_1_1NeuralNet.html#4cb52dae7b43d03fac73afca7b9f3a51">00068</a> <span class="keywordtype">int</span> <a class="code" href="classneuralpp_1_1NeuralNet.html#4cb52dae7b43d03fac73afca7b9f3a51">epochs</a>;
<a name="l00069"></a><a class="code" href="classneuralpp_1_1NeuralNet.html#4f88106c9e542c39eac43b4ca1974a2a">00069</a> <span class="keywordtype">int</span> <a class="code" href="classneuralpp_1_1NeuralNet.html#4f88106c9e542c39eac43b4ca1974a2a">ref_epochs</a>;
<a name="l00070"></a><a class="code" href="classneuralpp_1_1NeuralNet.html#6bd7be443e46b2fdbf1da2edb8e611ab">00070</a> <span class="keywordtype">double</span> <a class="code" href="classneuralpp_1_1NeuralNet.html#6bd7be443e46b2fdbf1da2edb8e611ab">l_rate</a>;
<a name="l00071"></a><a class="code" href="classneuralpp_1_1NeuralNet.html#327dbfdd72b0a74293f8f29630525aa3">00071</a> <span class="keywordtype">double</span> <a class="code" href="classneuralpp_1_1NeuralNet.html#327dbfdd72b0a74293f8f29630525aa3">threshold</a>;
<a name="l00072"></a><a class="code" href="classneuralpp_1_1NeuralNet.html#a9e4ff43427f56663739c4c7450de8ee">00072</a> std::vector&lt;double&gt; <a class="code" href="classneuralpp_1_1NeuralNet.html#a9e4ff43427f56663739c4c7450de8ee">expect</a>;
<a name="l00073"></a>00073
<a name="l00078"></a>00078 <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="l00079"></a>00079
<a name="l00085"></a>00085 <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="l00086"></a>00086
<a name="l00091"></a>00091 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="l00092"></a>00092
<a name="l00098"></a>00098 <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="l00099"></a>00099
<a name="l00105"></a>00105 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="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="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="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="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="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="l00111"></a>00111 <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="l00112"></a>00112
<a name="l00117"></a>00117 <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="l00118"></a>00118
<a name="l00124"></a>00124 <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="l00125"></a>00125
<a name="l00129"></a>00129 <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="l00130"></a>00130
<a name="l00131"></a>00131 <span class="keyword">public</span>:
<a name="l00132"></a><a class="code" href="classneuralpp_1_1NeuralNet.html#e2b4e8405f9d25edab395d61502bdba9">00132</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="l00133"></a><a class="code" href="classneuralpp_1_1NeuralNet.html#bbdaa1b6c0a1a95d2b18cd25fda2a266">00133</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="l00134"></a><a class="code" href="classneuralpp_1_1NeuralNet.html#fa9b2dbcbb39d0fc70f790ac24069a74">00134</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="l00135"></a>00135
<a name="l00139"></a><a class="code" href="classneuralpp_1_1NeuralNet.html#94c36c94060e785ea67a0014c4182f8f6d06b4fe9414a158c97aee1a3679a904">00139</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="l00140"></a>00140
<a name="l00144"></a><a class="code" href="classneuralpp_1_1NeuralNet.html#92b145f2f6f00bf1ba645ce2235882c2">00144</a> <a class="code" href="classneuralpp_1_1NeuralNet.html#92b145f2f6f00bf1ba645ce2235882c2" title="Empty constructor for the class - it just makes nothing.">NeuralNet</a>() {}
<a name="l00145"></a>00145
<a name="l00159"></a>00159 <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="l00160"></a>00160 <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="l00161"></a>00161
<a name="l00167"></a>00167 <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="l00168"></a>00168
<a name="l00174"></a>00174 <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="l00175"></a>00175
<a name="l00180"></a>00180 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="l00181"></a>00181
<a name="l00186"></a>00186 <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="l00187"></a>00187
<a name="l00192"></a>00192 <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="l00193"></a>00193
<a name="l00198"></a>00198 <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="l00199"></a>00199
<a name="l00206"></a>00206 <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="l00207"></a>00207
<a name="l00218"></a>00218 <span class="keywordtype">void</span> <a class="code" href="classneuralpp_1_1NeuralNet.html#a060e28b438613a6cc9e0895ddbc292b" title="DEPRECATED.">loadFromBinary</a> (<span class="keyword">const</span> std::string fname) <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="l00219"></a>00219
<a name="l00230"></a>00230 <span class="keywordtype">void</span> <a class="code" href="classneuralpp_1_1NeuralNet.html#520147d9b47b69565567bd3fdcfd8897" title="DEPRECATED.">saveToBinary</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="l00231"></a>00231
<a name="l00239"></a>00239 <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="l00240"></a>00240
<a name="l00245"></a>00245 <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="l00246"></a>00246
<a name="l00259"></a>00259 <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="l00260"></a>00260
<a name="l00265"></a>00265 <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="l00266"></a>00266 };
<a name="l00267"></a>00267
<a name="l00273"></a><a class="code" href="classneuralpp_1_1Synapsis.html">00273</a> <span class="keyword">class </span><a class="code" href="classneuralpp_1_1Synapsis.html" title="Class for managing synapsis.">Synapsis</a> {
<a name="l00274"></a><a class="code" href="classneuralpp_1_1Synapsis.html#617fdc4305f8f1850eac267a7ee22660">00274</a> <span class="keywordtype">double</span> <a class="code" href="classneuralpp_1_1Synapsis.html#617fdc4305f8f1850eac267a7ee22660">delta</a>;
<a name="l00275"></a><a class="code" href="classneuralpp_1_1Synapsis.html#65471cd6c9ef87609dfa4b0e5fafa708">00275</a> <span class="keywordtype">double</span> <a class="code" href="classneuralpp_1_1Synapsis.html#65471cd6c9ef87609dfa4b0e5fafa708">prev_delta</a>;
<a name="l00276"></a><a class="code" href="classneuralpp_1_1Synapsis.html#0bc523a8135ebbb5c0da932939d30ed7">00276</a> <span class="keywordtype">double</span> <a class="code" href="classneuralpp_1_1Synapsis.html#0bc523a8135ebbb5c0da932939d30ed7">weight</a>;
<a name="l00277"></a>00277
<a name="l00278"></a><a class="code" href="classneuralpp_1_1Synapsis.html#83d41c158054b08bd05051736e89a0ad">00278</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="l00279"></a><a class="code" href="classneuralpp_1_1Synapsis.html#fb219e05038fa0da20db1082ab0500be">00279</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="l00280"></a>00280
<a name="l00281"></a>00281 double (*<a class="code" href="classneuralpp_1_1Synapsis.html#2539b9eef2ff0f3522aea8d89e394f02">actv_f</a>)(double);
<a name="l00282"></a>00282
<a name="l00283"></a>00283 <span class="keyword">public</span>:
<a name="l00287"></a><a class="code" href="classneuralpp_1_1Synapsis.html#c7760b19c56e9f69994970311703c5fa">00287</a> <a class="code" href="classneuralpp_1_1Synapsis.html#c7760b19c56e9f69994970311703c5fa" title="Empty constructor (it does nothing).">Synapsis</a>() {}
<a name="l00288"></a>00288
<a name="l00295"></a>00295 <a class="code" href="classneuralpp_1_1Synapsis.html#c7760b19c56e9f69994970311703c5fa" title="Empty constructor (it does nothing).">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="l00296"></a>00296
<a name="l00304"></a>00304 <a class="code" href="classneuralpp_1_1Synapsis.html#c7760b19c56e9f69994970311703c5fa" title="Empty constructor (it does nothing).">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="l00305"></a>00305 <span class="keywordtype">double</span> w, <span class="keywordtype">double</span>(*a)(<span class="keywordtype">double</span>));
<a name="l00306"></a>00306
<a name="l00310"></a>00310 <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="l00311"></a>00311
<a name="l00315"></a>00315 <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="l00316"></a>00316
<a name="l00321"></a>00321 <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="l00322"></a>00322
<a name="l00328"></a>00328 <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="l00329"></a>00329
<a name="l00334"></a>00334 <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="l00335"></a>00335
<a name="l00340"></a>00340 <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="l00341"></a>00341
<a name="l00346"></a>00346 <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="l00347"></a>00347
<a name="l00358"></a>00358 <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="l00359"></a>00359 };
<a name="l00360"></a>00360
<a name="l00366"></a><a class="code" href="classneuralpp_1_1Neuron.html">00366</a> <span class="keyword">class </span><a class="code" href="classneuralpp_1_1Neuron.html" title="Class for managing neurons.">Neuron</a> {
<a name="l00367"></a><a class="code" href="classneuralpp_1_1Neuron.html#eec680c47272b2465e8d8a998c359853">00367</a> <span class="keywordtype">double</span> <a class="code" href="classneuralpp_1_1Neuron.html#eec680c47272b2465e8d8a998c359853">actv_val</a>;
<a name="l00368"></a><a class="code" href="classneuralpp_1_1Neuron.html#da75259de98b1a893c736666af6bfdc3">00368</a> <span class="keywordtype">double</span> <a class="code" href="classneuralpp_1_1Neuron.html#da75259de98b1a893c736666af6bfdc3">prop_val</a>;
<a name="l00369"></a><a class="code" href="classneuralpp_1_1Neuron.html#7b16632868821d73dedcb8edaf6dbbef">00369</a> <span class="keywordtype">double</span> <a class="code" href="classneuralpp_1_1Neuron.html#7b16632868821d73dedcb8edaf6dbbef">threshold</a>;
<a name="l00370"></a>00370
<a name="l00371"></a><a class="code" href="classneuralpp_1_1Neuron.html#bd07357465bb7b29bb344400e9e08710">00371</a> std::vector&lt; Synapsis &gt; <a class="code" href="classneuralpp_1_1Neuron.html#bd07357465bb7b29bb344400e9e08710">in</a>;
<a name="l00372"></a><a class="code" href="classneuralpp_1_1Neuron.html#982aceef324b7764e778d5949720bc55">00372</a> std::vector&lt; Synapsis &gt; <a class="code" href="classneuralpp_1_1Neuron.html#982aceef324b7764e778d5949720bc55">out</a>;
<a name="l00373"></a>00373
<a name="l00374"></a>00374 double (*<a class="code" href="classneuralpp_1_1Neuron.html#198ddd0d11a26d0052d52b787d6a0df0">actv_f</a>)(double);
<a name="l00375"></a>00375
<a name="l00376"></a>00376 <span class="keyword">public</span>:
<a name="l00383"></a>00383 <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="l00384"></a>00384
<a name="l00393"></a>00393 <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="l00394"></a>00394 <span class="keywordtype">double</span> (*a)(<span class="keywordtype">double</span>), <span class="keywordtype">double</span> th = 0.0);
<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#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="l00402"></a>00402
<a name="l00408"></a>00408 <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="l00409"></a>00409
<a name="l00414"></a>00414 <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="l00415"></a>00415
<a name="l00420"></a>00420 <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="l00421"></a>00421
<a name="l00426"></a>00426 <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="l00427"></a>00427
<a name="l00432"></a>00432 <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="l00433"></a>00433
<a name="l00434"></a>00434 <span class="keywordtype">void</span> <a class="code" href="classneuralpp_1_1Neuron.html#6fa3e8afc1c6e6e427773ba89a6fcb68">setSynIn</a> (<span class="keywordtype">size_t</span> n);
<a name="l00435"></a>00435 <span class="keywordtype">void</span> <a class="code" href="classneuralpp_1_1Neuron.html#d6ae3a93ecd11c345d931aee4ca248c1">setSynOut</a> (<span class="keywordtype">size_t</span> n);
<a name="l00436"></a>00436
<a name="l00441"></a>00441 <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="l00442"></a>00442
<a name="l00447"></a>00447 <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="l00448"></a>00448
<a name="l00452"></a>00452 <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="l00453"></a>00453
<a name="l00458"></a>00458 <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="l00459"></a>00459
<a name="l00464"></a>00464 <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="l00465"></a>00465
<a name="l00469"></a>00469 <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="l00470"></a>00470 };
<a name="l00471"></a>00471
<a name="l00477"></a><a class="code" href="classneuralpp_1_1Layer.html">00477</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="l00478"></a><a class="code" href="classneuralpp_1_1Layer.html#8188cb5c264e6021cee9979b968a0305">00478</a> std::vector&lt;Neuron&gt; <a class="code" href="classneuralpp_1_1Layer.html#8188cb5c264e6021cee9979b968a0305">elements</a>;
<a name="l00479"></a><a class="code" href="classneuralpp_1_1Layer.html#02cf4efe1da02a7404d25375c85ed71f">00479</a> <span class="keywordtype">double</span> <a class="code" href="classneuralpp_1_1Layer.html#02cf4efe1da02a7404d25375c85ed71f">threshold</a>;
<a name="l00480"></a>00480
<a name="l00481"></a>00481 void (*<a class="code" href="classneuralpp_1_1Layer.html#c023a15a16353d0b4f44060a159f550f">update_weights</a>)();
<a name="l00482"></a>00482 double (*<a class="code" href="classneuralpp_1_1Layer.html#824367da29f92253a027a7c5b4a4405e">actv_f</a>)(double);
<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="l00484"></a>00484 <span class="keyword">public</span>:
<a name="l00492"></a>00492 <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="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="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="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="l00502"></a>00502 <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="l00503"></a>00503
<a name="l00509"></a>00509 <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="l00510"></a>00510
<a name="l00515"></a>00515 <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="l00516"></a>00516
<a name="l00521"></a>00521 <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="l00522"></a>00522
<a name="l00526"></a>00526 <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="l00527"></a>00527
<a name="l00531"></a>00531 <span class="keywordtype">size_t</span> <a class="code" href="classneuralpp_1_1Layer.html#7ca71ed62fbe9c1e9c0fb6a8dcaf76f0">size</a>() <span class="keyword">const</span>;
<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="l00534"></a><a class="code" href="structneuralpp_1_1netrecord.html">00534</a> <span class="keyword">struct </span><a class="code" href="structneuralpp_1_1netrecord.html">netrecord</a> {
<a name="l00535"></a><a class="code" href="structneuralpp_1_1netrecord.html#e1f480bfef05033accef40f77c09fa87">00535</a> <span class="keywordtype">int</span> <a class="code" href="structneuralpp_1_1netrecord.html#e1f480bfef05033accef40f77c09fa87">input_size</a>;
<a name="l00536"></a><a class="code" href="structneuralpp_1_1netrecord.html#3c1728ac66c37f6ac85c404d4f55552e">00536</a> <span class="keywordtype">int</span> hidden_size;
<a name="l00537"></a><a class="code" href="structneuralpp_1_1netrecord.html#95f2b0651dd3a0e5e7201ff354e401b4">00537</a> <span class="keywordtype">int</span> <a class="code" href="structneuralpp_1_1netrecord.html#95f2b0651dd3a0e5e7201ff354e401b4">output_size</a>;
<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="l00539"></a><a class="code" href="structneuralpp_1_1netrecord.html#ab0149ed5ea0694e88213a07cd4427d1">00539</a> <span class="keywordtype">int</span> <a class="code" href="structneuralpp_1_1netrecord.html#ab0149ed5ea0694e88213a07cd4427d1">epochs</a>;
<a name="l00540"></a><a class="code" href="structneuralpp_1_1netrecord.html#a4f793a39a40144e811fef4d3d2d2b30">00540</a> <span class="keywordtype">double</span> <a class="code" href="structneuralpp_1_1netrecord.html#a4f793a39a40144e811fef4d3d2d2b30">l_rate</a>;
<a name="l00541"></a><a class="code" href="structneuralpp_1_1netrecord.html#dcc44fde3f67058d26ef2d5cbd0904e6">00541</a> <span class="keywordtype">double</span> <a class="code" href="structneuralpp_1_1netrecord.html#dcc44fde3f67058d26ef2d5cbd0904e6">ex</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>
<a name="l00543"></a>00543
<a name="l00544"></a><a class="code" href="structneuralpp_1_1neuronrecord.html">00544</a> <span class="keyword">struct </span><a class="code" href="structneuralpp_1_1neuronrecord.html">neuronrecord</a> {
<a name="l00545"></a><a class="code" href="structneuralpp_1_1neuronrecord.html#30b298a95939b88b565fefc2dc57e89d">00545</a> <span class="keywordtype">double</span> prop;
<a name="l00546"></a><a class="code" href="structneuralpp_1_1neuronrecord.html#15201b190584987255d81d4b7e773375">00546</a> <span class="keywordtype">double</span> <a class="code" href="structneuralpp_1_1neuronrecord.html#15201b190584987255d81d4b7e773375">actv</a>;
<a name="l00547"></a>00547 };
<a name="l00548"></a>00548
<a name="l00549"></a><a class="code" href="structneuralpp_1_1synrecord.html">00549</a> <span class="keyword">struct </span><a class="code" href="structneuralpp_1_1synrecord.html">synrecord</a> {
<a name="l00550"></a><a class="code" href="structneuralpp_1_1synrecord.html#81a7dbc97eecbf5bc85cac46373a78d2">00550</a> <span class="keywordtype">double</span> w;
<a name="l00551"></a><a class="code" href="structneuralpp_1_1synrecord.html#3a862082dfa0edffce84936818bab374">00551</a> <span class="keywordtype">double</span> <a class="code" href="structneuralpp_1_1synrecord.html#3a862082dfa0edffce84936818bab374">d</a>;
<a name="l00552"></a>00552 };
<a name="l00553"></a>00553
<a name="l00554"></a><a class="code" href="namespaceneuralpp_1_1neuralutils.html">00554</a> <span class="keyword">namespace </span>neuralutils {
<a name="l00561"></a>00561 std::vector&lt;double&gt; <a class="code" href="namespaceneuralpp_1_1neuralutils.html#68719b3d63ca48ed264e1b730a1aaa4a" title="Split a string into a vector of doubles, given a delimitator.">split</a> (<span class="keywordtype">char</span> delim, std::string str);
<a name="l00562"></a>00562
<a name="l00568"></a>00568 std::vector&lt;std::string&gt; <a class="code" href="namespaceneuralpp_1_1neuralutils.html#1d887e4bcc7ef2d50cbeca984767a78b" title="Split the lines of a string.">splitLines</a> (std::string str);
<a name="l00569"></a>00569
<a name="l00574"></a>00574 <span class="keywordtype">void</span> <a class="code" href="namespaceneuralpp_1_1neuralutils.html#f7932c25bd82b19173d2f3d2e5cef488" title="Convert the characters of a string to lower case.">toLower</a> (std::string&amp; str);
<a name="l00575"></a>00575
<a name="l00580"></a>00580 <span class="keywordtype">void</span> <a class="code" href="namespaceneuralpp_1_1neuralutils.html#265b22d1a6110646b42693b96c21ca8b" title="Convert the characters of a string to upper case.">toUpper</a> (std::string&amp; str);
<a name="l00581"></a>00581 }
<a name="l00582"></a>00582 }
<a name="l00583"></a>00583
<a name="l00584"></a>00584 <span class="preprocessor">#endif</span>
<a name="l00585"></a>00585 <span class="preprocessor"></span>
</pre></div></div>
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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

@ -28,6 +28,8 @@
<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 class="memItemLeft" nowrap align="right" valign="top">namespace &nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespaceneuralpp_1_1neuralutils.html">neuralpp::neuralutils</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_1NeuralNet.html">neuralpp::NeuralNet</a></td></tr>
@ -48,17 +50,27 @@
<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">neuralpp::synrecord</a></td></tr>
<tr><td colspan="2"><br><h2>Defines</h2></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#839a9222721835f53c5b248241f535f4">RAND</a>&nbsp;&nbsp;&nbsp;(double) ( (rand() / (RAND_MAX/2)) - 1)</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#839a9222721835f53c5b248241f535f4">RAND</a>&nbsp;&nbsp;&nbsp;(double) ( (rand() / 10.0) / ((double) RAND_MAX) )</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;1.0</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="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>
<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="namespaceneuralpp_1_1neuralutils.html#68719b3d63ca48ed264e1b730a1aaa4a">neuralpp::neuralutils::split</a> (char delim, std::string str)</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Split a string into a vector of doubles, given a delimitator. <a href="#68719b3d63ca48ed264e1b730a1aaa4a"></a><br></td></tr>
<tr><td class="memItemLeft" nowrap align="right" valign="top">std::vector&lt; std::string &gt;&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespaceneuralpp_1_1neuralutils.html#1d887e4bcc7ef2d50cbeca984767a78b">neuralpp::neuralutils::splitLines</a> (std::string str)</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Split the lines of a string. <a href="#1d887e4bcc7ef2d50cbeca984767a78b"></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="namespaceneuralpp_1_1neuralutils.html#f7932c25bd82b19173d2f3d2e5cef488">neuralpp::neuralutils::toLower</a> (std::string &amp;str)</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Convert the characters of a string to lower case. <a href="#f7932c25bd82b19173d2f3d2e5cef488"></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="namespaceneuralpp_1_1neuralutils.html#265b22d1a6110646b42693b96c21ca8b">neuralpp::neuralutils::toUpper</a> (std::string &amp;str)</td></tr>
<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Convert the characters of a string to upper case. <a href="#265b22d1a6110646b42693b96c21ca8b"></a><br></td></tr>
</table>
<hr><h2>Define Documentation</h2>
<a class="anchor" name="05e2bb5b9fc32f0b6b4d84fe43177d72"></a><!-- doxytag: member="neural++.hpp::BETA0" ref="05e2bb5b9fc32f0b6b4d84fe43177d72" args="" -->
@ -66,14 +78,12 @@
<div class="memproto">
<table class="memname">
<tr>
<td class="memname">#define BETA0&nbsp;&nbsp;&nbsp;1.0 </td>
<td class="memname">#define BETA0&nbsp;&nbsp;&nbsp;0.8 </td>
</tr>
</table>
</div>
<div class="memdoc">
<p>
Initial value for the inertial momentum of the synapses.
<p>
</div>
@ -83,20 +93,18 @@ Initial value for the inertial momentum of the synapses.
<div class="memproto">
<table class="memname">
<tr>
<td class="memname">#define RAND&nbsp;&nbsp;&nbsp;(double) ( (rand() / (RAND_MAX/2)) - 1) </td>
<td class="memname">#define RAND&nbsp;&nbsp;&nbsp;(double) ( (rand() / 10.0) / ((double) RAND_MAX) ) </td>
</tr>
</table>
</div>
<div class="memdoc">
<p>
Default rand value: |sin(rand)|, always &gt;= 0 and &lt;= 1.
<p>
</div>
</div><p>
</div>
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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

@ -31,44 +31,52 @@
<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>
<a name="l00017"></a>00017 <span class="preprocessor">#include &lt;cstdio&gt;</span>
<a name="l00018"></a>00018 <span class="preprocessor">#include &lt;cstring&gt;</span>
<a name="l00019"></a>00019 <span class="preprocessor">#include &lt;exception&gt;</span>
<a name="l00020"></a>00020
<a name="l00021"></a>00021 <span class="keyword">namespace </span>neuralpp {
<a name="l00026"></a><a class="code" href="classneuralpp_1_1NetworkFileNotFoundException.html">00026</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="l00027"></a>00027 <span class="keyword">public</span>:
<a name="l00028"></a><a class="code" href="classneuralpp_1_1NetworkFileNotFoundException.html#9603eebdb841f06c9b1007e65cba60f6">00028</a> <a class="code" href="classneuralpp_1_1NetworkFileNotFoundException.html#9603eebdb841f06c9b1007e65cba60f6">NetworkFileNotFoundException</a>() {}
<a name="l00029"></a><a class="code" href="classneuralpp_1_1NetworkFileNotFoundException.html#24cde7729ab22d343f36e638cfc40702">00029</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="l00030"></a>00030 };
<a name="l00031"></a>00031
<a name="l00037"></a><a class="code" href="classneuralpp_1_1NetworkFileWriteException.html">00037</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="l00038"></a>00038 <span class="keyword">public</span>:
<a name="l00039"></a><a class="code" href="classneuralpp_1_1NetworkFileWriteException.html#83bc897b0ea11a384e0839a39e9fdb48">00039</a> <a class="code" href="classneuralpp_1_1NetworkFileWriteException.html#83bc897b0ea11a384e0839a39e9fdb48">NetworkFileWriteException</a>() {}
<a name="l00040"></a><a class="code" href="classneuralpp_1_1NetworkFileWriteException.html#c8802852cb38d5edf6f490ff3acb6078">00040</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="l00041"></a>00041 };
<a name="l00042"></a>00042
<a name="l00047"></a><a class="code" href="classneuralpp_1_1InvalidXMLException.html">00047</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="l00048"></a><a class="code" href="classneuralpp_1_1InvalidXMLException.html#e0c63b17f7b5b0df20d8361bc9ee92b4">00048</a> <span class="keywordtype">char</span> *<a class="code" href="classneuralpp_1_1InvalidXMLException.html#e0c63b17f7b5b0df20d8361bc9ee92b4">error</a>;
<a name="l00049"></a>00049
<a name="l00050"></a>00050 <span class="keyword">public</span>:
<a name="l00051"></a><a class="code" href="classneuralpp_1_1InvalidXMLException.html#793d311be88606908abf8c5be1348586">00051</a> <a class="code" href="classneuralpp_1_1InvalidXMLException.html#793d311be88606908abf8c5be1348586">InvalidXMLException</a>(<span class="keyword">const</span> <span class="keywordtype">char</span> *err = <span class="stringliteral">" "</span>) {
<a name="l00052"></a>00052 <a class="code" href="classneuralpp_1_1InvalidXMLException.html#e0c63b17f7b5b0df20d8361bc9ee92b4">error</a> = <span class="keyword">new</span> <span class="keywordtype">char</span>[strlen(err)+40];
<a name="l00053"></a>00053 sprintf (<a class="code" href="classneuralpp_1_1InvalidXMLException.html#e0c63b17f7b5b0df20d8361bc9ee92b4">error</a>, <span class="stringliteral">"Attempt to load an invalid XML file: %s"</span>, err);
<a name="l00054"></a>00054 }
<a name="l00055"></a>00055
<a name="l00056"></a><a class="code" href="classneuralpp_1_1InvalidXMLException.html#4a8b81678ed0c319e1715ab5ef9112da">00056</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> <a class="code" href="classneuralpp_1_1InvalidXMLException.html#e0c63b17f7b5b0df20d8361bc9ee92b4">error</a>; }
<a name="l00057"></a>00057 };
<a name="l00058"></a>00058
<a name="l00064"></a><a class="code" href="classneuralpp_1_1NetworkIndexOutOfBoundsException.html">00064</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="l00065"></a>00065 <span class="keyword">public</span>:
<a name="l00066"></a><a class="code" href="classneuralpp_1_1NetworkIndexOutOfBoundsException.html#07141d2225ea9f2d486e755a3660d594">00066</a> <a class="code" href="classneuralpp_1_1NetworkIndexOutOfBoundsException.html#07141d2225ea9f2d486e755a3660d594">NetworkIndexOutOfBoundsException</a>() {}
<a name="l00067"></a><a class="code" href="classneuralpp_1_1NetworkIndexOutOfBoundsException.html#8b65d77cb375a0aa40d5a9ea692bd5c3">00067</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="l00068"></a>00068 };
<a name="l00069"></a>00069
<a name="l00075"></a><a class="code" href="classneuralpp_1_1InvalidSynapticalWeightException.html">00075</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="l00076"></a>00076 <span class="keyword">public</span>:
<a name="l00077"></a><a class="code" href="classneuralpp_1_1InvalidSynapticalWeightException.html#42e54de0ef9d9f711a483287f4f95916">00077</a> <a class="code" href="classneuralpp_1_1InvalidSynapticalWeightException.html#42e54de0ef9d9f711a483287f4f95916">InvalidSynapticalWeightException</a>() {}
<a name="l00078"></a><a class="code" href="classneuralpp_1_1InvalidSynapticalWeightException.html#8d374dd7e8363b2551ae6e306b11473a">00078</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="l00079"></a>00079 };
<a name="l00080"></a>00080 }
<a name="l00081"></a>00081
<a name="l00082"></a>00082 <span class="preprocessor">#endif</span>
<a name="l00083"></a>00083 <span class="preprocessor"></span>
</pre></div></div>
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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</div>
</div>
<div class="contents">
<h1>neural++_exception.hpp File Reference</h1><code>#include &lt;exception&gt;</code><br>
<h1>neural++_exception.hpp File Reference</h1><code>#include &lt;cstdio&gt;</code><br>
<code>#include &lt;cstring&gt;</code><br>
<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">
@ -43,7 +45,7 @@
<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>
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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<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>
</table></div>
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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@ -198,7 +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>
</div>
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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<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>
</table></div>
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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@ -528,7 +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>
</div>
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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@ -34,7 +34,7 @@
<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>
</table></div>
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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@ -196,7 +196,7 @@
<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>
</div>
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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<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>
</table></div>
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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@ -177,7 +177,7 @@
<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>
</div>
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 2009 for Neural++ by&nbsp;
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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>
</table></div>
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 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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@ -310,7 +310,7 @@
<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>
</div>
<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 20:53:42 2009 for Neural++ by&nbsp;
<hr size="1"><address style="text-align: right;"><small>Generated on Fri Sep 4 11:25:49 2009 for Neural++ by&nbsp;
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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>
</table></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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<img src="doxygen.png" alt="doxygen" align="middle" border="0"></a> 1.5.6 </small></address>
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<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>
</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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<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>
</table></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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@ -146,7 +146,7 @@
<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>
</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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<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>
</table></div>
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