Commit 3c0ec38b authored by Michal Kravcenko's avatar Michal Kravcenko

added a constant file and more neuron classes

parent 6d7ca604
......@@ -5,32 +5,32 @@
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......
cmake_minimum_required(VERSION 3.0)
project(NeuronLib)
set (NeuronLib_VERSION_MAJOR 0)
set (NeuronLib_VERSION_MINOR 1)
message ("Before enable language")
enable_language(Fortran)
if (WIN32)
message ("cmake for " ${CMAKE_Fortran_COMPILER})
set (CMAKE_FORTRAN_COMPILER ${CMAKE_Fortran_COMPILER})
project(4Neuro FORTRAN)
project(4Neuro)
else ()
project(4Neuro)
endif ()
......
add_library(neuron SHARED Neuron/neuron.cpp Neuron/neuron.h Neuron/NeuronBinary.cpp Neuron/NeuronBinary.h Neuron/NeuronLinear.cpp Neuron/NeuronLinear.h Neuron/NeuronLogistic.cpp Neuron/NeuronLogistic.h Neuron/NeuronTanh.cpp Neuron/NeuronTanh.h)
add_library(neuron SHARED Neuron/neuron.cpp Neuron/neuron.h Neuron/NeuronBinary.cpp Neuron/NeuronBinary.h Neuron/NeuronLinear.cpp Neuron/NeuronLinear.h Neuron/NeuronLogistic.cpp Neuron/NeuronLogistic.h Neuron/NeuronTanh.cpp Neuron/NeuronTanh.h constants.h)
......@@ -17,6 +17,5 @@ void NeuronBinary::activate() {
else{
this->state = 0.0;
}
}
......@@ -20,7 +20,7 @@ public:
* @param threshold Denotes when the neuron is activated
* When neuron potential exceeds 'threshold' value it becomes excited
*/
explicit NeuronBinary(double threshold);
explicit NeuronBinary(double threshold = 0.0);
/**
* Performs the activation function and stores the result into the 'state' property
......
......@@ -3,3 +3,32 @@
//
#include "NeuronLinear.h"
NeuronLinear::NeuronLinear(double a, double b) {
this->activation_function_parameters = new double[2];
this->activation_function_parameters[0] = a;
this->activation_function_parameters[1] = b;
}
void NeuronLinear::activate() {
this->state = this->activation_function_parameters[0] * this->potential + this->activation_function_parameters[1];
}
double NeuronLinear::activation_function_get_partial_derivative(int param_idx) {
if(param_idx == 0){
return this->potential;
}
else{
return 1.0;
}
}
double NeuronLinear::activation_function_get_derivative() {
return this->activation_function_parameters[0];
}
\ No newline at end of file
......@@ -5,9 +5,43 @@
#ifndef INC_4NEURO_NEURONLINEAR_H
#define INC_4NEURO_NEURONLINEAR_H
#include "neuron.h"
class NeuronLinear {
/**
* Linear neuron class - uses activation function in the form f(x)=a*x + b,
* 'x' being the neuron's potential
*/
class NeuronLinear:Neuron {
public:
/**
* Constructs the object of the Linear neuron with activation function
* f(x) = a * x + b
* @param a First coefficient, stored in activation_function_parameters[0]
* @param b Second coefficient, stored in activation_function_parameters[1]
*/
explicit NeuronLinear(double a = 0.0, double b = 0.0);
/**
* Evaluates 'a*x + b' and stores the result into the 'state' property
*/
void activate() override;
/**
* Calculates the partial derivative of the activation function
* f(x) = a*x + b
* @param param_idx Index of the parameter to calculate derivative of
* @return Partial derivative of the activation function according to the
* 'param_idx'-th parameter. For 'param_idx'=0 returns 'x', otherwise
* returns 1
*/
double activation_function_get_partial_derivative(int param_idx) override;
/**
* Calculates d/dx of (a*x + b)
* @return a
*/
double activation_function_get_derivative() override;
};
......
......@@ -2,4 +2,59 @@
// Created by fluffymoo on 11.6.18.
//
#include "NeuronLogistic.h"
NeuronLogistic::NeuronLogistic(double a, double b) {
this->activation_function_parameters = new double[2];
this->activation_function_parameters[0] = a;
this->activation_function_parameters[1] = b;
}
void NeuronLogistic::activate() {
double a = this->activation_function_parameters[0];
double b = this->activation_function_parameters[1];
double x = this->potential;
double ex = std::pow(E, b - x);
this->state = std::pow(1.0 + ex, -a);
}
double NeuronLogistic::activation_function_get_partial_derivative(int param_idx) {
double a = this->activation_function_parameters[0];
double b = this->activation_function_parameters[1];
double x = this->potential;
if(param_idx == 0){
double ex = std::pow(E, b - x);
double exa= -std::pow(ex + 1.0, -a);
return exa * std::log(ex + 1.0);
}
else{
double ex = std::pow(E, b - x);
double ex2 = std::pow(ex + 1.0, -a - 1.0);
return -a * ex * ex2;
}
}
double NeuronLogistic::activation_function_get_derivative() {
double a = this->activation_function_parameters[0];
double b = this->activation_function_parameters[1];
double x = this->potential;
double ex = std::pow(E, b - x);
double ex2 = std::pow(ex + 1.0, -a - 1.0);
return a * ex * ex2;
}
\ No newline at end of file
......@@ -5,9 +5,38 @@
#ifndef INC_4NEURO_NEURONLOGISTIC_H
#define INC_4NEURO_NEURONLOGISTIC_H
#include <cmath>
#include "neuron.h"
#include "../constants.h"
class NeuronLogistic {
class NeuronLogistic:Neuron {
/**
* Constructs the object of the Logistic neuron with activation function
* f(x) = (1 + e^(-x + b))^(-a)
* @param a First coefficient, stored in activation_function_parameters[0]
* @param b Second coefficient, stored in activation_function_parameters[1]
*/
explicit NeuronLogistic(double a = 0.0, double b = 0.0);
/**
* Evaluates '(1 + e^(-x + b))^(-a)' and stores the result into the 'state' property
*/
void activate() override;
/**
* Calculates the partial derivative of the activation function
* f(x) = (1 + e^(-x + b))^(-a)
* @param param_idx Index of the parameter to calculate derivative of
* @return Partial derivative of the activation function according to the
* 'param_idx'-th parameter.
*/
double activation_function_get_partial_derivative(int param_idx) override;
/**
* Calculates d/dx of (1 + e^(-x + b))^(-a)
* @return a * e^(b - x) * [e^(b - x) + 1]^(-a)
*/
double activation_function_get_derivative() override;
};
......
......@@ -96,6 +96,12 @@ public:
*/
virtual double activation_function_get_partial_derivative(int param_idx) = 0;
/**
* Calculates the derivative with respect to the argument, ie the 'potential'
* @return f'(x), where 'f(x)' is the activation function and 'x' = 'potential'
*/
virtual double activation_function_get_derivative( ) = 0;
/**
* Adjusts the parameter with index 'param_idx' of the activation function
* by the value prescribed by 'value'
......
//
// Created by fluffymoo on 11.6.18.
//
#ifndef INC_4NEURO_CONSTANTS_H
#define INC_4NEURO_CONSTANTS_H
#define E 2.7182818284590
#define PI 3.14159265358979323846
#endif //INC_4NEURO_CONSTANTS_H
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