[딥러닝] C++로 구현하는 뉴런 기초

출처: https://www.youtube.com/watch?v=lg-PZ-zIr98

#include <iostream>

#define MAX2(a,b) (a) > (b) ? (a) : (b)

class Neuron

{

public:

double w_; // weight of one input

double b_; // bias

double getAct(const double& x)

{

// for linear or identity activation functions

return x;

// for ReLU activation functions

//return MAX2(0.0, x);

}

double feedForward(const double& input)

{

// output y = f(\sigma) , 

// \sigma = w_ * input x + b

// for multiple inputs,

// \sigma = w0_ * x0_ + w1_ * x1_ + ... + b

const double sigma = w_ * input + b_;

return getAct(sigma);

}

};

void main()

{

Neuron my_neuron;

my_neuron.w_ = 2.0;

my_neuron.b_ = 1.0;

std::cout << "input = 0.0  " << my_neuron.feedForward(0.0) << std::endl;

std::cout << "input = 1.0  "<< my_neuron.feedForward(1.0) << std::endl;

std::cout << "input = 2.0  " << my_neuron.feedForward(2.0) << std::endl;

std::cout << "input = 3.0  " << my_neuron.feedForward(3.0) << std::endl;

}