chopfield.cpp

This fiel shows how to use Hopfield networks

#include "CHopfield.h"

CHopfield::CHopfield() {
	// Seed the random engine.
	srand((unsigned)time(NULL));


	// Allocate all necessary memory.
	m_piOutputs =	 (int *)calloc(ELEMENTS, sizeof(int));
	m_piThresholds = (int *)calloc(ELEMENTS, sizeof(int));
	m_hiWeights =	 (int**)calloc(ELEMENTS, sizeof(int*));

	for (int i=0; i<ELEMENTS; i++) {
		m_piThresholds[i] = 0;		// Set the threshold.
		
		// Allocate additional memory for the weights.
		m_hiWeights[i] = (int *)calloc(ELEMENTS, sizeof(int));
	}

	ImageAltered = 0;
}

CHopfield::~CHopfield() {}
		
bool CHopfield::ReadData(char *filename) {
	ifstream data(filename);
	
	if (!data) return false;

	int temp;
	for(int n=0;n<NUMDATA;n++) {
		for(int y=0;y<RESY;y++) {
			for (int x=0;x<RESX;x++) {
				data >> temp;
				
				m_iInputs[n][y*RESX+x] = _bipolar(temp);
			}
		}
	}

	return true;
}

void CHopfield::TrainNet() {
	// Firstly, calculate the weights.
	for(int i=0;i<ELEMENTS;i++) {
		for (int j=0;j<ELEMENTS;j++) {
			int weight=0;

			if (i != j) {
				for (int k=0;k<NUMDATA;k++) {
					weight += m_iInputs[k][i] * m_iInputs[k][j];
				}
			}

			m_hiWeights[i][j] = weight;
		}
	}
}

void CHopfield::Run(int ind) {
	// Set the inputs.
	for(int j=0;j<ELEMENTS;j++) m_piOutputs[j] = m_iInputs[ind][j];

	AdvanceNet();					// Advance the net.
}

void CHopfield::RunNet() {
	for(int i=0;i<NUMDATA;i++) {
		// Set the inputs.
		for(int j=0;j<ELEMENTS;j++) m_piOutputs[j] = m_iInputs[i][j];

		AdvanceNet();				// Advance the net.
	}
}

bool CHopfield::AdvanceNeuron(int neuron) {
	int  net = 0;
	bool changed = false;

	for (int j=0;j<ELEMENTS;j++)
		net += m_hiWeights[neuron][j] * m_piOutputs[j];

	int result;
	if (net != m_piThresholds[neuron]) {
		if (net < m_piThresholds[neuron]) result = -1;
		else if (net > m_piThresholds[neuron]) result = 1;

		if (result != m_piOutputs[neuron]) {
			m_piOutputs[neuron] = result;
			changed = true;
			
			if (ImageAltered) {
				int x = (neuron % RESY),
					y = (neuron / RESY);

				ImageAltered(x,y);
			}
		}
	}

	return changed;
}

void CHopfield::AdvanceNet() {
	int iter = 0, last = 0;

	do {
		iter++;
		int rndunit = rand();
		rndunit %= ELEMENTS;

		if (AdvanceNeuron(rndunit)) {
			last = iter;
		}

	} while (iter - last < 10*ELEMENTS);
}

void CHopfield::SetCallback(_callback cb) {
	ImageAltered = cb;
}

void CHopfield::GetOutput(bool *result, int num) {
	for (int i=0;i<RESY;i++) {
		for (int j=0;j<RESX;j++) {
			result[num*ELEMENTS+(i*RESY+j)] = _binary(m_piOutputs[i*RESY+j]);
		}
	}
}