trainingsetneuralchromosome.java

VHDL制作的ann的code

/*
 * Encog Neural Network and Bot Library for Java v1.x
 * http://www.heatonresearch.com/encog/
 * http://code.google.com/p/encog-java/
 * 
 * Copyright 2008, Heaton Research Inc., and individual contributors.
 * See the copyright.txt in the distribution for a full listing of 
 * individual contributors.
 *
 * This is free software; you can redistribute it and/or modify it
 * under the terms of the GNU Lesser General Public License as
 * published by the Free Software Foundation; either version 2.1 of
 * the License, or (at your option) any later version.
 *
 * This software is distributed in the hope that it will be useful,
 * but WITHOUT ANY WARRANTY; without even the implied warranty of
 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
 * Lesser General Public License for more details.
 *
 * You should have received a copy of the GNU Lesser General Public
 * License along with this software; if not, write to the Free
 * Software Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
 * 02110-1301 USA, or see the FSF site: http://www.fsf.org.
 */
package org.encog.neural.networks.training.genetic;

import org.encog.neural.networks.BasicNetwork;

/**
 * TrainingSetNeuralChromosome: Implements a chromosome that allows a
 * feedforward neural network to be trained using a genetic algorithm. The
 * network is trained using training sets.
 * 
 * The chromosome for a feed forward neural network is the weight and threshold
 * matrix.
 */
public class TrainingSetNeuralChromosome extends NeuralChromosome {

	/**
	 * The constructor, takes a list of cities to set the initial "genes" to.
	 * 
	 * @param genetic
	 *            The genetic algorithm used with this chromosome.
	 * @param network
	 *            The neural network to train.
	 */
	public TrainingSetNeuralChromosome(
			final TrainingSetNeuralGeneticAlgorithm genetic,
			final BasicNetwork network) {
		setGeneticAlgorithm(genetic);
		setNetwork(network);

		initGenes(network.getWeightMatrixSize());
		updateGenes();
	}

	/**
	 * Calculate the cost for this chromosome.
	 */
	@Override
	public void calculateCost() {
		// update the network with the new gene values
		updateNetwork();

		// update the cost with the new genes
		setCost(getNetwork()
				.calculateError(getGeneticAlgorithm().getTraining()));

	}

	/**
	 * Get the genetic algorithm in use.
	 * @return The genetic algorithm in use.
	 */
	public TrainingSetNeuralGeneticAlgorithm getGeneticAlgorithm() {
		return (TrainingSetNeuralGeneticAlgorithm) super.getGeneticAlgorithm();
	}

	/**
	 * Set all genes.
	 * 
	 * @param list
	 *            A list of genes.
	 * @throws NeuralNetworkException
	 */
	@Override
	public void setGenes(final Double[] list) {

		// copy the new genes
		super.setGenes(list);

		calculateCost();

	}
}