/**
* Copyright 2010 Neuroph Project http://neuroph.sourceforge.net
*
* 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.
*/
package org.neuroph.nnet.learning;
import org.neuroph.core.NeuralNetwork;
import org.neuroph.core.Neuron;
import org.neuroph.nnet.comp.ThresholdNeuron;
/**
* Perceptron learning rule for perceptron neural networks.
*
* @author Zoran Sevarac <sevarac@gmail.com>
*/
public class PerceptronLearning extends LMS {
/**
* The class fingerprint that is set to indicate serialization
* compatibility with a previous version of the class.
*/
private static final long serialVersionUID = 1L;
/**
* Creates new PerceptronLearning instance
*/
public PerceptronLearning() {
super();
}
/**
* This method implements weights update procedure for the single neuron
* In addition to weights change in LMS it applies change to neuron's threshold
*
* @param neuron
* neuron to update weights
*/
@Override
protected void updateNeuronWeights(Neuron neuron) {
// adjust the input connection weights with method from superclass
super.updateNeuronWeights(neuron);
// and adjust the neurons threshold
ThresholdNeuron thresholdNeuron = (ThresholdNeuron)neuron;
// get neurons error
double neuronError = thresholdNeuron.getError();
// get the neurons threshold
double thresh = thresholdNeuron.getThresh();
// calculate new threshold value
thresh = thresh - this.learningRate * neuronError;
// apply the new threshold
thresholdNeuron.setThresh(thresh);
}
}