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< div class = "navpath" > < a class = "el" href = "namespaceneuralpp.html" > neuralpp< / a > ::< a class = "el" href = "classneuralpp_1_1Layer.html" > Layer< / a >
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< h1 > neuralpp::Layer Class Reference< / h1 > <!-- doxytag: class="neuralpp::Layer" --> Class for managing layers of neurons.
< a href = "#_details" > More...< / a >
< p >
< code > #include < < a class = "el" href = "neural_09_09_8hpp-source.html" > neural++.hpp< / a > > < / code >
< p >
< p >
< a href = "classneuralpp_1_1Layer-members.html" > List of all members.< / a > < table border = "0" cellpadding = "0" cellspacing = "0" >
< tr > < td > < / td > < / tr >
< tr > < td colspan = "2" > < br > < h2 > Public Member Functions< / h2 > < / td > < / tr >
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< tr > < td class = "memItemLeft" nowrap align = "right" valign = "top" > < / td > < td class = "memItemRight" valign = "bottom" > < a class = "el" href = "classneuralpp_1_1Layer.html#a235767701b5e9dcf28c5e9e0d04cb0b" > Layer< / a > (size_t sz, double(*a)(double), double th=0.0)< / td > < / tr >
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< tr > < td class = "mdescLeft" > < / td > < td class = "mdescRight" > Constructor. < a href = "#a235767701b5e9dcf28c5e9e0d04cb0b" > < / a > < br > < / td > < / tr >
< tr > < td class = "memItemLeft" nowrap align = "right" valign = "top" > < / td > < td class = "memItemRight" valign = "bottom" > < a class = "el" href = "classneuralpp_1_1Layer.html#d79f684523f8a6e086b962c8eef37623" > Layer< / a > (std::vector< < a class = "el" href = "classneuralpp_1_1Neuron.html" > Neuron< / a > > & neurons, double(*a)(double), double th=0.0)< / td > < / tr >
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< tr > < td class = "mdescLeft" > < / td > < td class = "mdescRight" > Alternative constructor. < a href = "#d79f684523f8a6e086b962c8eef37623" > < / a > < br > < / td > < / tr >
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< tr > < td class = "memItemLeft" nowrap align = "right" valign = "top" > < a class = "el" href = "classneuralpp_1_1Neuron.html" > Neuron< / a > & < / td > < td class = "memItemRight" valign = "bottom" > < a class = "el" href = "classneuralpp_1_1Layer.html#45ff7554830558155c6fbce3b6827122" > operator[]< / a > (size_t i) throw (NetworkIndexOutOfBoundsException)< / td > < / tr >
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< tr > < td class = "mdescLeft" > < / td > < td class = "mdescRight" > Redefinition for operator []. < a href = "#45ff7554830558155c6fbce3b6827122" > < / a > < br > < / td > < / tr >
< tr > < td class = "memItemLeft" nowrap align = "right" valign = "top" > void < / td > < td class = "memItemRight" valign = "bottom" > < a class = "el" href = "classneuralpp_1_1Layer.html#ac33444fde14633fa1ad4acb024ad150" > link< / a > (< a class = "el" href = "classneuralpp_1_1Layer.html" > Layer< / a > & l)< / td > < / tr >
< tr > < td class = "mdescLeft" > < / td > < td class = "mdescRight" > It links a layer to another. < a href = "#ac33444fde14633fa1ad4acb024ad150" > < / a > < br > < / td > < / tr >
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< tr > < td class = "memItemLeft" nowrap align = "right" valign = "top" > void < / td > < td class = "memItemRight" valign = "bottom" > < a class = "el" href = "classneuralpp_1_1Layer.html#88ceffc23f02a9dc24d4355767b7cca7" > setInput< / a > (std::vector< double > v)< / td > < / tr >
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< tr > < td class = "mdescLeft" > < / td > < td class = "mdescRight" > Set the input values for the neurons of the layer (just use it for the input layer). < a href = "#88ceffc23f02a9dc24d4355767b7cca7" > < / a > < br > < / td > < / tr >
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< tr > < td class = "memItemLeft" nowrap align = "right" valign = "top" > void < / td > < td class = "memItemRight" valign = "bottom" > < a class = "el" href = "classneuralpp_1_1Layer.html#fcfd306039dbaf91c9e2dcc8fc1f1ce1" > propagate< / a > ()< / td > < / tr >
< tr > < td class = "mdescLeft" > < / td > < td class = "mdescRight" > It propagates its activation values to the output layers. < a href = "#fcfd306039dbaf91c9e2dcc8fc1f1ce1" > < / a > < br > < / td > < / tr >
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< tr > < td class = "memItemLeft" nowrap align = "right" valign = "top" > size_t < / td > < td class = "memItemRight" valign = "bottom" > < a class = "el" href = "classneuralpp_1_1Layer.html#7ca71ed62fbe9c1e9c0fb6a8dcaf76f0" > size< / a > () const < / td > < / tr >
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< tr > < td colspan = "2" > < br > < h2 > Private Attributes< / h2 > < / td > < / tr >
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< tr > < td class = "memItemLeft" nowrap align = "right" valign = "top" > std::vector< < a class = "el" href = "classneuralpp_1_1Neuron.html" > Neuron< / a > > < / td > < td class = "memItemRight" valign = "bottom" > < a class = "el" href = "classneuralpp_1_1Layer.html#8188cb5c264e6021cee9979b968a0305" > elements< / a > < / td > < / tr >
< tr > < td class = "memItemLeft" nowrap align = "right" valign = "top" > double < / td > < td class = "memItemRight" valign = "bottom" > < a class = "el" href = "classneuralpp_1_1Layer.html#02cf4efe1da02a7404d25375c85ed71f" > threshold< / a > < / td > < / tr >
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< tr > < td class = "memItemLeft" nowrap align = "right" valign = "top" > void(* < / td > < td class = "memItemRight" valign = "bottom" > < a class = "el" href = "classneuralpp_1_1Layer.html#c023a15a16353d0b4f44060a159f550f" > update_weights< / a > )()< / td > < / tr >
< tr > < td class = "memItemLeft" nowrap align = "right" valign = "top" > double(* < / td > < td class = "memItemRight" valign = "bottom" > < a class = "el" href = "classneuralpp_1_1Layer.html#824367da29f92253a027a7c5b4a4405e" > actv_f< / a > )(double)< / td > < / tr >
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< hr > < a name = "_details" > < / a > < h2 > Detailed Description< / h2 >
Class for managing layers of neurons.
< p >
Don't use this class directly unless you know what you're doing, use < a class = "el" href = "classneuralpp_1_1NeuralNet.html" title = "Main project's class." > NeuralNet< / a > instead < hr > < h2 > Constructor & Destructor Documentation< / h2 >
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< a class = "anchor" name = "a235767701b5e9dcf28c5e9e0d04cb0b" > < / a > <!-- doxytag: member="neuralpp::Layer::Layer" ref="a235767701b5e9dcf28c5e9e0d04cb0b" args="(size_t sz, double(*a)(double), double th=0.0)" -->
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< td class = "memname" > neuralpp::Layer::Layer < / td >
< td > (< / td >
< td class = "paramtype" > size_t < / td >
< td class = "paramname" > < em > sz< / em > , < / td >
< / tr >
< tr >
< td class = "paramkey" > < / td >
< td > < / td >
< td class = "paramtype" > double(*)(double) < / td >
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< td class = "paramname" > < em > a< / em > , < / td >
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< td class = "paramkey" > < / td >
< td > < / td >
< td class = "paramtype" > double < / td >
< td class = "paramname" > < em > th< / em > = < code > 0.0< / code > < / td > < td > < / td >
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< / tr >
< tr >
< td > < / td >
< td > )< / td >
< td > < / td > < td > < / td > < td > < / td >
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Constructor.
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< dl compact > < dt > < b > Parameters:< / b > < / dt > < dd >
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< tr > < td valign = "top" > < / td > < td valign = "top" > < em > sz< / em > < / td > < td > Size of the layer < / td > < / tr >
< tr > < td valign = "top" > < / td > < td valign = "top" > < em > a< / em > < / td > < td > Activation function < / td > < / tr >
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< tr > < td valign = "top" > < / td > < td valign = "top" > < em > th< / em > < / td > < td > Threshold, value in [0,1] that establishes how much a neuron must be 'sensitive' on variations of the input values < / td > < / tr >
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< a class = "anchor" name = "d79f684523f8a6e086b962c8eef37623" > < / a > <!-- doxytag: member="neuralpp::Layer::Layer" ref="d79f684523f8a6e086b962c8eef37623" args="(std::vector< Neuron > &neurons, double(*a)(double), double th=0.0)" -->
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< td class = "memname" > neuralpp::Layer::Layer < / td >
< td > (< / td >
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< td class = "paramtype" > std::vector< < a class = "el" href = "classneuralpp_1_1Neuron.html" > Neuron< / a > > & < / td >
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< td class = "paramname" > < em > neurons< / em > , < / td >
< / tr >
< tr >
< td class = "paramkey" > < / td >
< td > < / td >
< td class = "paramtype" > double(*)(double) < / td >
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< td class = "paramname" > < em > a< / em > , < / td >
< / tr >
< tr >
< td class = "paramkey" > < / td >
< td > < / td >
< td class = "paramtype" > double < / td >
< td class = "paramname" > < em > th< / em > = < code > 0.0< / code > < / td > < td > < / td >
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< / tr >
< tr >
< td > < / td >
< td > )< / td >
< td > < / td > < td > < / td > < td > < / td >
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Alternative constructor.
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It directly gets a vector of neurons to build the layer < dl compact > < dt > < b > Parameters:< / b > < / dt > < dd >
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< tr > < td valign = "top" > < / td > < td valign = "top" > < em > neurons< / em > < / td > < td > Vector of neurons to be included in the layer < / td > < / tr >
< tr > < td valign = "top" > < / td > < td valign = "top" > < em > a< / em > < / td > < td > Activation function < / td > < / tr >
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< tr > < td valign = "top" > < / td > < td valign = "top" > < em > th< / em > < / td > < td > Threshold, value in [0,1] that establishes how much a neuron must be 'sensitive' on variations of the input values < / td > < / tr >
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< / table >
< / dl >
< / div >
< / div > < p >
< hr > < h2 > Member Function Documentation< / h2 >
< a class = "anchor" name = "45ff7554830558155c6fbce3b6827122" > < / a > <!-- doxytag: member="neuralpp::Layer::operator[]" ref="45ff7554830558155c6fbce3b6827122" args="(size_t i)" -->
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< td class = "memname" > < a class = "el" href = "classneuralpp_1_1Neuron.html" > Neuron< / a > & neuralpp::Layer::operator[] < / td >
< td > (< / td >
< td class = "paramtype" > size_t < / td >
< td class = "paramname" > < em > i< / em > < / td >
< td > ) < / td >
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< td > throw (< a class = "el" href = "classneuralpp_1_1NetworkIndexOutOfBoundsException.html" > NetworkIndexOutOfBoundsException< / a > )< / td >
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Redefinition for operator [].
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It gets the neuron at < em > i< / em > < dl compact > < dt > < b > Parameters:< / b > < / dt > < dd >
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< tr > < td valign = "top" > < / td > < td valign = "top" > < em > i< / em > < / td > < td > Index of the neuron to get in the layer < / td > < / tr >
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< dl class = "return" compact > < dt > < b > Returns:< / b > < / dt > < dd > Reference to the i-th neuron < / dd > < / dl >
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< a class = "anchor" name = "ac33444fde14633fa1ad4acb024ad150" > < / a > <!-- doxytag: member="neuralpp::Layer::link" ref="ac33444fde14633fa1ad4acb024ad150" args="(Layer &l)" -->
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< td class = "memname" > void neuralpp::Layer::link < / td >
< td > (< / td >
< td class = "paramtype" > < a class = "el" href = "classneuralpp_1_1Layer.html" > Layer< / a > & < / td >
< td class = "paramname" > < em > l< / em > < / td >
< td > ) < / td >
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It links a layer to another.
< p >
< dl compact > < dt > < b > Parameters:< / b > < / dt > < dd >
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< tr > < td valign = "top" > < / td > < td valign = "top" > < em > l< / em > < / td > < td > < a class = "el" href = "classneuralpp_1_1Layer.html" title = "Class for managing layers of neurons." > Layer< / a > to connect to the current as input layer < / td > < / tr >
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< a class = "anchor" name = "88ceffc23f02a9dc24d4355767b7cca7" > < / a > <!-- doxytag: member="neuralpp::Layer::setInput" ref="88ceffc23f02a9dc24d4355767b7cca7" args="(std::vector< double > v)" -->
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< td class = "memname" > void neuralpp::Layer::setInput < / td >
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< td > (< / td >
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< td class = "paramtype" > std::vector< double > < / td >
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< td class = "paramname" > < em > v< / em > < / td >
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Set the input values for the neurons of the layer (just use it for the input layer).
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< p >
< dl compact > < dt > < b > Parameters:< / b > < / dt > < dd >
< table border = "0" cellspacing = "2" cellpadding = "0" >
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< tr > < td valign = "top" > < / td > < td valign = "top" > < em > v< / em > < / td > < td > Vector containing the input values < / td > < / tr >
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< a class = "anchor" name = "fcfd306039dbaf91c9e2dcc8fc1f1ce1" > < / a > <!-- doxytag: member="neuralpp::Layer::propagate" ref="fcfd306039dbaf91c9e2dcc8fc1f1ce1" args="()" -->
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< td class = "memname" > void neuralpp::Layer::propagate < / td >
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< td > (< / td >
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It propagates its activation values to the output layers.
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< a class = "anchor" name = "7ca71ed62fbe9c1e9c0fb6a8dcaf76f0" > < / a > <!-- doxytag: member="neuralpp::Layer::size" ref="7ca71ed62fbe9c1e9c0fb6a8dcaf76f0" args="() const " -->
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< td class = "memname" > size_t neuralpp::Layer::size < / td >
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< td > (< / td >
< td class = "paramname" > < / td >
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< td > const< / td >
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< dl class = "return" compact > < dt > < b > Returns:< / b > < / dt > < dd > Number of neurons in the layer < / dd > < / dl >
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< / div >
< / div > < p >
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< hr > < h2 > Member Data Documentation< / h2 >
< a class = "anchor" name = "8188cb5c264e6021cee9979b968a0305" > < / a > <!-- doxytag: member="neuralpp::Layer::elements" ref="8188cb5c264e6021cee9979b968a0305" args="" -->
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< td class = "memname" > std::vector< < a class = "el" href = "classneuralpp_1_1Neuron.html" > Neuron< / a > > < a class = "el" href = "classneuralpp_1_1Layer.html#8188cb5c264e6021cee9979b968a0305" > neuralpp::Layer::elements< / a > < code > [private]< / code > < / td >
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< a class = "anchor" name = "02cf4efe1da02a7404d25375c85ed71f" > < / a > <!-- doxytag: member="neuralpp::Layer::threshold" ref="02cf4efe1da02a7404d25375c85ed71f" args="" -->
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< td class = "memname" > double < a class = "el" href = "classneuralpp_1_1Layer.html#02cf4efe1da02a7404d25375c85ed71f" > neuralpp::Layer::threshold< / a > < code > [private]< / code > < / td >
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< a class = "anchor" name = "c023a15a16353d0b4f44060a159f550f" > < / a > <!-- doxytag: member="neuralpp::Layer::update_weights" ref="c023a15a16353d0b4f44060a159f550f" args=")()" -->
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< td class = "memname" > void(* < a class = "el" href = "classneuralpp_1_1Layer.html#c023a15a16353d0b4f44060a159f550f" > neuralpp::Layer::update_weights< / a > )()< code > [private]< / code > < / td >
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< a class = "anchor" name = "824367da29f92253a027a7c5b4a4405e" > < / a > <!-- doxytag: member="neuralpp::Layer::actv_f" ref="824367da29f92253a027a7c5b4a4405e" args=")(double)" -->
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< hr > The documentation for this class was generated from the following file:< ul >
< li > < a class = "el" href = "neural_09_09_8hpp-source.html" > neural++.hpp< / a > < / ul >
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2009-09-04 11:27:14 +02:00
< hr size = "1" > < address style = "text-align: right;" > < small > Generated on Fri Sep 4 11:25:49 2009 for Neural++ by
2009-08-09 11:17:39 +02:00
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< img src = "doxygen.png" alt = "doxygen" align = "middle" border = "0" > < / a > 1.5.6 < / small > < / address >
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