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Michal Kravcenko
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/**
* DESCRIPTION OF THE CLASS
*
* @author Martin Beseda
* @author Martin Mrovec
* @author Michal Kravčenko
* @date 2017 - 2018
*/
#ifndef INC_4NEURO_NEURONLOGISTIC_H
#define INC_4NEURO_NEURONLOGISTIC_H
Martin Beseda
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#include "../settings.h"
Martin Beseda
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#include "Neuron.h"
Martin Beseda
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namespace lib4neuro {
class NeuronLogistic : public NeuronDifferentiable {
Martin Beseda
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public:
/**
* Struct used to access private properties from
* the serialization function
*/
struct access;
/**
* Constructs the object of the Logistic neuron with activation function
* f(x) = (1 + e^(-x + b))^(-1)
*/
LIB4NEURO_API explicit NeuronLogistic();
/**
* Evaluates '(1 + e^(-x + b))^(-1)' and stores the result into the 'state' property
*/
LIB4NEURO_API virtual double activate(double x, double b) override;
/**
* Calculates the partial derivative of the activation function
* f(x) = (1 + e^(-x + b))^(-1)
* @return Partial derivative of the activation function according to the
* bias, returns: -e^(b - x)/(e^(b - x) + 1)^2
*/
LIB4NEURO_API virtual double activation_function_eval_derivative_bias(double x, double b) override;
/**
* Calculates d/dx of (1 + e^(-x + b))^(-1)
* @return e^(b - x)/(e^(b - x) + 1)^2
*/
LIB4NEURO_API virtual double activation_function_eval_derivative(double x, double b) override;
/**
* Returns a pointer to a Neuron with derivative as its activation function
* @return
*/
LIB4NEURO_API virtual NeuronLogistic *get_derivative() override;
};
class NeuronLogistic_d1 : public NeuronLogistic {
public:
/**
* Struct used to access private properties from
* the serialization function
*/
struct access;
/**
* Constructs the object of the Logistic neuron with activation function
* f(x) = e^(b - x)/(e^(b - x) + 1)^2
* @param[in] b Bias
*/
LIB4NEURO_API explicit NeuronLogistic_d1();
/**
* Evaluates 'e^(b - x)/(e^(b - x) + 1)^2' and returns the result
*/
LIB4NEURO_API virtual double activate(double x, double b) override;
/**
* Calculates the partial derivative of the activation function
* f(x) = e^(b - x)/(e^(b - x) + 1)^2
* @return Partial derivative of the activation function according to the
* bias, returns: (e^(b + x) (e^x - e^b))/(e^b + e^x)^3
*/
LIB4NEURO_API virtual double activation_function_eval_derivative_bias(double x, double b) override;
/**
* Calculates d/dx of e^(b - x)*(1 + e^(b - x))^(-2)
* @return (e^(b + x) (e^b - e^x))/(e^b + e^x)^3
*/
LIB4NEURO_API virtual double activation_function_eval_derivative(double x, double b) override;
/**
* Returns a pointer to a Neuron with derivative as its activation function
* @return
*/
LIB4NEURO_API virtual NeuronLogistic *get_derivative() override;
};
class NeuronLogistic_d2 : public NeuronLogistic_d1 {
public:
/**
* Struct used to access private properties from
* the serialization function
*/
struct access;
/**
* Constructs the object of the Logistic neuron with activation function
* f(x) = (e^(b + x) (e^b - e^x))/(e^b + e^x)^3
*/
LIB4NEURO_API explicit NeuronLogistic_d2();
/**
* Evaluates '(e^(b + x) (e^b - e^x))/(e^b + e^x)^3' and returns the result
*/
LIB4NEURO_API virtual double activate(double x, double b) override;
/**
* Calculates the partial derivative of the activation function
* f(x) = (e^(b + x) (e^b - e^x))/(e^b + e^x)^3
* @return Partial derivative of the activation function according to the
* bias, returns: -(e^(b + x) (-4 e^(b + x) + e^(2 b) + e^(2 x)))/(e^b + e^x)^4
*/
LIB4NEURO_API virtual double activation_function_eval_derivative_bias(double x, double b) override;
/**
* Calculates d/dx of (e^(b + x) (e^b - e^x))/(e^b + e^x)^3
* @return (e^(b + x) (-4 e^(b + x) + e^(2 b) + e^(2 x)))/(e^b + e^x)^4
*/
LIB4NEURO_API virtual double activation_function_eval_derivative(double x, double b) override;
/**
*
* @return
*/
LIB4NEURO_API virtual NeuronLogistic *get_derivative() override;
};
}
#endif //INC_4NEURO_NEURONLOGISTIC_H