Files
NeuralNetworkLib/include/NeuralNetwork/Recurrent/Neuron.h

124 lines
2.8 KiB
C++

#pragma once
#include "../Neuron.h"
#include <NeuralNetwork/ActivationFunction/Sigmoid.h>
#include <NeuralNetwork/BasisFunction/Linear.h>
#include <vector>
#include <sstream>
#include <iomanip>
#include <limits>
namespace NeuralNetwork {
namespace Recurrent {
class Network;
/**
* @author Tomas Cernik (Tom.Cernik@gmail.com)
* @brief Class of recurrent neuron.
*/
class Neuron : public NeuralNetwork::Neuron
{
public:
Neuron(unsigned long _id=0,const float& _bias = 0): NeuralNetwork::Neuron(), basis(new BasisFunction::Linear),
activation(new ActivationFunction::Sigmoid(-4.9)),
id_(_id),bias(_bias),weights(_id+1),_output(0),_value(0) {
}
Neuron(const Neuron &r): NeuralNetwork::Neuron(), basis(r.basis->clone()), activation(r.activation->clone()),id_(r.id_),
bias(r.bias), weights(r.weights), _output(r._output), _value(r._value) {
}
virtual ~Neuron() {
delete basis;
delete activation;
};
virtual std::string stringify(const std::string &prefix="") const override;
Recurrent::Neuron& operator=(const NeuralNetwork::Recurrent::Neuron&r) {
id_=r.id_;
bias=r.bias;
weights=r.weights;
basis=r.basis->clone();
activation=r.activation->clone();
return *this;
}
virtual long unsigned int id() const override {
return id_;
};
/**
* @brief Gets weight
* @param n is neuron
*/
virtual float getWeight(const NeuralNetwork::Neuron &n) const override {
return weights[n.id()];
}
/**
* @brief Sets weight
* @param n is neuron
* @param w is new weight for input neuron n
*/
virtual void setWeight(const NeuralNetwork::Neuron& n ,const float &w) override {
if(weights.size()<n.id()+1) {
weights.resize(n.id()+1);
}
weights[n.id()]=w;
}
/**
* @brief Returns output of neuron
*/
virtual float output() const override {
return _output;
}
/**
* @brief Returns input of neuron
*/
virtual float value() const override {
return _value;
}
/**
* @brief Function sets bias for neuron
* @param _bias is new bias (initial value for neuron)
*/
virtual void setBias(const float &_bias) override {
bias=_bias;
}
/**
* @brief Function returns bias for neuron
*/
virtual float getBias() const override {
return bias;
}
float operator()(const std::vector<float>& inputs) {
//compute value
_value=basis->operator()(weights,inputs)+bias;
//compute output
_output=activation->operator()(_value);
return _output;
}
protected:
BasisFunction::BasisFunction *basis;
ActivationFunction::ActivationFunction *activation;
unsigned long id_;
float bias;
std::vector<float> weights;
float _output;
float _value;
};
}
}