Neuro/Neuron.cpp

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#pragma once
#include "Neuron.h"
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Neuron::Neuron(double value)
: outputValue(value)
, gradient(0)
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{
}
void Neuron::setOutputValue(double value)
{
outputValue = value;
}
double Neuron::transferFunction(double inputValue)
{
return std::tanh(inputValue);
}
double Neuron::transferFunctionDerivative(double inputValue)
{
return 1.0 - (inputValue * inputValue);
}
void Neuron::feedForward(double inputValue)
{
outputValue = transferFunction(inputValue);
}
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double Neuron::getWeightedOutputValue(unsigned int outputNeuron) const
{
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if (outputNeuron < outputWeights.size())
{
return outputValue * outputWeights[outputNeuron];
}
return 0.0;
}
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void Neuron::createRandomOutputWeights(size_t numberOfWeights)
{
outputWeights.clear();
for (unsigned int i = 0; i < numberOfWeights; ++i)
{
outputWeights.push_back(std::rand() / (double)RAND_MAX);
}
}
double Neuron::getOutputValue() const
{
return outputValue;
}
void Neuron::calcOutputGradients(double targetValue)
{
double delta = targetValue - outputValue;
gradient = delta * transferFunctionDerivative(outputValue);
}