Perceptron

Perceptron.cpp

#include <stdio.h>
#include <stdlib.h>
#include "Perceptron.h"
#include <math.h>

const float c = 0.01;

Perceptron::Perceptron(int n) {
    weights = new float[n];
    
    for (int i = 0; i < n; i++) {
        weights[i] = generateRandFloatValue();
    }
}

Perceptron::~Perceptron()
{
    delete weights;
}

void Perceptron::getWeights(float *out,int weightNum)
{
    for (int i = 0; i < weightNum; i++) {
        out[i] = weights[i];
    }
}

float Perceptron::feedforward(float *inputs, int inputNum)
{
    float sum = 0;
    for (int i = 0; i < inputNum; i++) {
        sum += inputs[i]*weights[i];
    }
    return activate(sum);
}

float Perceptron::activate(float sum)
{
#if 0
    return 1/(1+exp(-sum)); //standard sigmoid
#else
    if (sum > 0) {
        return 1.0f;
    } else {
        return -1.0f;
    }
#endif
}

void Perceptron::train(float *inputs,int inputNum, int desired)
{
    int guess = feedforward(inputs, inputNum);
    float error = desired - guess;
    for (int i = 0; i < inputNum; i++) {
        weights[i] += c * error * inputs[i];
    }
}

float generateRandFloatValue()
{
    float r = (float)rand()/(float)RAND_MAX;
    return r * 2.0 - 1.0;
}

ported from example 10.1 of The Nature of code
http://natureofcode.com/book/chapter-10-neural-networks/