/*
* Encog(tm) Examples v2.4
* http://www.heatonresearch.com/encog/
* http://code.google.com/p/encog-java/
*
* Copyright 2008-2010 by Heaton Research Inc.
*
* Released under the LGPL.
*
* 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.
*
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*/
package org.encog.examples.neural.util;
import org.encog.neural.data.NeuralDataSet;
import org.encog.neural.data.basic.BasicNeuralDataSet;
/**
* Utility class that presents the XOR operator as a serial stream of values.
* This is used to predict the next value in the XOR sequence. This provides a
* simple stream of numbers that can be predicted.
*
* @author jeff
*
*/
public class TemporalXOR {
/**
* 1 xor 0 = 1, 0 xor 0 = 0, 0 xor 1 = 1, 1 xor 1 = 0
*/
public static final double[] SEQUENCE = { 1.0, 0.0, 1.0, 0.0, 0.0, 0.0,
0.0, 1.0, 1.0, 1.0, 1.0, 0.0 };
private double[][] input;
private double[][] ideal;
public NeuralDataSet generate(final int count) {
this.input = new double[count][1];
this.ideal = new double[count][1];
for (int i = 0; i < this.input.length; i++) {
this.input[i][0] = TemporalXOR.SEQUENCE[i
% TemporalXOR.SEQUENCE.length];
this.ideal[i][0] = TemporalXOR.SEQUENCE[(i + 1)
% TemporalXOR.SEQUENCE.length];
}
return new BasicNeuralDataSet(this.input, this.ideal);
}
}