/**
* 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;
import org.neuroph.core.Layer;
import org.neuroph.core.NeuralNetwork;
import org.neuroph.nnet.learning.InstarLearning;
import org.neuroph.util.ConnectionFactory;
import org.neuroph.util.LayerFactory;
import org.neuroph.util.NeuralNetworkFactory;
import org.neuroph.util.NeuralNetworkType;
import org.neuroph.util.NeuronProperties;
import org.neuroph.util.TransferFunctionType;
/**
* Instar neural network with Instar learning rule.
* @author Zoran Sevarac <sevarac@gmail.com>
*/
public class Instar extends NeuralNetwork {
/**
* 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 Instar with specified number of input neurons.
*
* @param inputNeuronsCount
* number of neurons in input layer
*/
public Instar(int inputNeuronsCount) {
this.createNetwork(inputNeuronsCount);
}
/**
* Creates Instar architecture with specified number of input neurons
*
* @param inputNeuronsCount
* number of neurons in input layer
*/
private void createNetwork(int inputNeuronsCount ) {
// set network type
this.setNetworkType(NeuralNetworkType.INSTAR);
// init neuron settings for this type of network
NeuronProperties neuronProperties = new NeuronProperties();
neuronProperties.setProperty("transferFunction", TransferFunctionType.STEP);
// create input layer
Layer inputLayer = LayerFactory.createLayer(inputNeuronsCount, neuronProperties);
this.addLayer(inputLayer);
// createLayer output layer
neuronProperties.setProperty("transferFunction", TransferFunctionType.STEP);
Layer outputLayer = LayerFactory.createLayer(1, neuronProperties);
this.addLayer(outputLayer);
// create full conectivity between input and output layer
ConnectionFactory.fullConnect(inputLayer, outputLayer);
// set input and output cells for this network
NeuralNetworkFactory.setDefaultIO(this);
// set appropriate learning rule for this network
this.setLearningRule(new InstarLearning());
}
}