/*
* Encog(tm) Core 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.neural.pattern;
import org.encog.engine.network.activation.ActivationFunction;
import org.encog.mathutil.rbf.RBFEnum;
import org.encog.ml.MLMethod;
import org.encog.neural.rbf.RBFNetwork;
/**
* A radial basis function (RBF) network uses several radial basis functions to
* provide a more dynamic hidden layer activation function than many other types
* of neural network. It consists of a input, output and hidden layer.
*
* @author jheaton
*
*/
public class RadialBasisPattern implements NeuralNetworkPattern {
private RBFEnum rbfType = RBFEnum.Gaussian;
/**
* The number of input neurons to use. Must be set, default to invalid -1
* value.
*/
private int inputNeurons = -1;
/**
* The number of hidden neurons to use. Must be set, default to invalid -1
* value.
*/
private int outputNeurons = -1;
/**
* The number of hidden neurons to use. Must be set, default to invalid -1
* value.
*/
private int hiddenNeurons = -1;
/**
* Add the hidden layer, this should be called once, as a RBF has a single
* hidden layer.
*
* @param count
* The number of neurons in the hidden layer.
*/
public final void addHiddenLayer(final int count) {
if (this.hiddenNeurons != -1) {
throw new PatternError("A RBF network usually has a single "
+ "hidden layer.");
} else {
this.hiddenNeurons = count;
}
}
/**
* Clear out any hidden neurons.
*/
public final void clear() {
this.hiddenNeurons = -1;
}
/**
* Generate the RBF network.
*
* @return The neural network.
*/
public final MLMethod generate() {
RBFNetwork result = new RBFNetwork(inputNeurons, this.hiddenNeurons ,outputNeurons,this.rbfType);
return result;
}
/**
* Set the activation function, this is an error. The activation function
* may not be set on a RBF layer.
*
* @param activation
* The new activation function.
*/
public final void setActivationFunction(final ActivationFunction activation) {
throw new PatternError( "Can't set the activation function for "
+ "a radial basis function network.");
}
/**
* Set the number of input neurons.
*
* @param count
* The number of input neurons.
*/
public final void setInputNeurons(final int count) {
this.inputNeurons = count;
}
/**
* Set the number of output neurons.
*
* @param count
* The number of output neurons.
*/
public final void setOutputNeurons(final int count) {
this.outputNeurons = count;
}
public final void setRBF(RBFEnum type) {
this.rbfType = type;
}
}