/*
* Encog(tm) Examples v3.0 - Java Version
* http://www.heatonresearch.com/encog/
* http://code.google.com/p/encog-java/
* Copyright 2008-2011 Heaton Research, Inc.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
* For more information on Heaton Research copyrights, licenses
* and trademarks visit:
* http://www.heatonresearch.com/copyright
*/
package org.encog.examples.neural.bam;
import org.encog.ml.data.specific.BiPolarNeuralData;
import org.encog.neural.bam.BAM;
import org.encog.neural.networks.NeuralDataMapping;
/**
* Simple class to recognize some patterns with a Bidirectional
* Associative Memory (BAM) Neural Network.
* This is very loosely based on a an example by Karsten Kutza,
* written in C on 1996-01-24.
* http://www.neural-networks-at-your-fingertips.com/bam.html
*
* I translated it to Java and adapted it to use Encog for neural
* network processing. I mainly kept the patterns from the
* original example.
*
*/
public class BidirectionalAssociativeMemory {
public static final String[] NAMES = { "TINA ", "ANTJE", "LISA " };
public static final String[] NAMES2 = { "TINE ", "ANNJE", "RITA " };
public static final String[] PHONES = { "6843726", "8034673", "7260915" };
public static final int IN_CHARS = 5;
public static final int OUT_CHARS = 7;
public static final int BITS_PER_CHAR = 6;
public static final char FIRST_CHAR = ' ';
public static final int INPUT_NEURONS = (IN_CHARS * BITS_PER_CHAR);
public static final int OUTPUT_NEURONS = (OUT_CHARS * BITS_PER_CHAR);
public BiPolarNeuralData stringToBipolar(String str)
{
BiPolarNeuralData result = new BiPolarNeuralData(str.length()*BITS_PER_CHAR);
int currentIndex = 0;
for(int i=0;i<str.length();i++)
{
char ch = Character.toUpperCase(str.charAt(i));
int idx = ch-FIRST_CHAR;
int place = 1;
for( int j=0;j<BITS_PER_CHAR;j++)
{
boolean value = (idx&place)>0;
result.setData(currentIndex++,value);
place*=2;
}
}
return result;
}
public String bipolalToString(BiPolarNeuralData data)
{
StringBuilder result = new StringBuilder();
int j,a,p;
for (int i=0; i<(data.size() / BITS_PER_CHAR); i++) {
a = 0;
p = 1;
for (j=0; j<BITS_PER_CHAR; j++) {
if( data.getBoolean(i*BITS_PER_CHAR+j) )
a+=p;
p *= 2;
}
result.append((char)(a + FIRST_CHAR));
}
return result.toString();
}
public BiPolarNeuralData randomBiPolar(int size)
{
BiPolarNeuralData result = new BiPolarNeuralData(size);
for(int i=0;i<size;i++)
{
if(Math.random()>0.5)
result.setData(i,-1);
else
result.setData(i,1);
}
return result;
}
public String mappingToString(NeuralDataMapping mapping)
{
StringBuilder result = new StringBuilder();
result.append( bipolalToString((BiPolarNeuralData)mapping.getFrom()) );
result.append(" -> ");
result.append( bipolalToString((BiPolarNeuralData)mapping.getTo()) );
return result.toString();
}
public void runBAM(BAM logic, NeuralDataMapping data )
{
StringBuilder line = new StringBuilder();
line.append(mappingToString(data));
logic.compute(data);
line.append(" | ");
line.append(mappingToString(data));
System.out.println(line.toString());
}
public void run()
{
BAM logic = new BAM(INPUT_NEURONS, OUTPUT_NEURONS);
// train
for(int i=0;i<NAMES.length;i++)
{
logic.addPattern(
stringToBipolar(NAMES[i]),
stringToBipolar(PHONES[i]));
}
// test
for(int i=0;i<NAMES.length;i++)
{
NeuralDataMapping data = new NeuralDataMapping(
stringToBipolar(NAMES[i]),
randomBiPolar(OUT_CHARS*BITS_PER_CHAR));
runBAM(logic, data);
}
System.out.println();
for(int i=0;i<PHONES.length;i++)
{
NeuralDataMapping data = new NeuralDataMapping(
stringToBipolar(PHONES[i]),
randomBiPolar(IN_CHARS*BITS_PER_CHAR) );
runBAM(logic, data);
}
System.out.println();
for(int i=0;i<NAMES.length;i++)
{
NeuralDataMapping data = new NeuralDataMapping(
stringToBipolar(NAMES2[i]),
randomBiPolar(OUT_CHARS*BITS_PER_CHAR));
runBAM(logic, data);
}
}
public static void main(String[] args) {
BidirectionalAssociativeMemory program = new BidirectionalAssociativeMemory();
program.run();
}
}