/** * 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.Connection; import org.neuroph.core.NeuralNetwork; import org.neuroph.core.Neuron; /** * Oja learning rule wich is a modification of unsupervised hebbian learning. * @author Zoran Sevarac <sevarac@gmail.com> */ public class OjaLearning extends UnsupervisedHebbianLearning{ /** * The class fingerprint that is set to indicate serialization * compatibility with a previous version of the class. */ private static final long serialVersionUID = 1L; /** * Creates an instance of OjaLearning algorithm */ public OjaLearning() { super(); } /** * This method implements weights update procedure for the single neuron * * @param neuron * neuron to update weights */ @Override protected void updateNeuronWeights(Neuron neuron) { double output = neuron.getOutput(); for(Connection connection : neuron.getInputConnections()) { double input = connection.getInput(); double weight = connection.getWeight().getValue(); double deltaWeight = (input - output*weight) * output * this.learningRate; connection.getWeight().inc(deltaWeight); } } }