GTK+ IOStream
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#include <NeuralNetwork.H>
Public Member Functions | |
TanhLayer (int inputSize, int outputSize) | |
template<typename Derived > | |
TanhLayer (const Eigen::MatrixBase< Derived > &weightsIn, const Eigen::MatrixBase< Derived > &biasIn) | |
virtual | ~TanhLayer (void) |
Destructor. More... | |
virtual Eigen::Matrix< TYPE, Eigen::Dynamic, 1 > & | activate (const Eigen::Matrix< TYPE, Eigen::Dynamic, 1 > &input) |
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NeuralLayer (int inputSize, int outputSize) | |
template<typename Derived > | |
NeuralLayer (const Eigen::MatrixBase< Derived > &weightsIn, const Eigen::MatrixBase< Derived > &biasIn) | |
virtual | ~NeuralLayer (void) |
Destructor. More... | |
Additional Inherited Members | |
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Eigen::Matrix< TYPE, Eigen::Dynamic, 1 > | output |
The output from this layer. More... | |
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Eigen::Matrix< TYPE, Eigen::Dynamic, Eigen::Dynamic > | weights |
The neural weights for this layer. More... | |
Eigen::Matrix< TYPE, Eigen::Dynamic, 1 > | bias |
The biases for this layer. More... | |
Implements a neural layer with an scaled and offset tanh activation function
TYPE | the precision of the data to use, e.g. float, double |
Definition at line 119 of file NeuralNetwork.H.
Generate a neural layer of particular size
inputSize | The number of the inputs |
outputSize | The number of outputs |
Definition at line 125 of file NeuralNetwork.H.
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inline |
Generate a neural layer of particular size providing the weights
weightsIn | The weights to set |
biasIn | The biases to set |
Derived | is used by Eigen's Curiously recurring template pattern (CRTP) |
Definition at line 134 of file NeuralNetwork.H.
Destructor.
Definition at line 138 of file NeuralNetwork.H.
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inlinevirtual |
The sigmoidal activation function
Evaluate the neural network using the sigmoid as the activation function
input | The input to this layer |
Reimplemented from NeuralLayer< TYPE >.
Definition at line 145 of file NeuralNetwork.H.