/***********************************************************************
This file is part of KEEL-software, the Data Mining tool for regression,
classification, clustering, pattern mining and so on.
Copyright (C) 2004-2010
F. Herrera (herrera@decsai.ugr.es)
L. S�nchez (luciano@uniovi.es)
J. Alcal�-Fdez (jalcala@decsai.ugr.es)
S. Garc�a (sglopez@ujaen.es)
A. Fern�ndez (alberto.fernandez@ujaen.es)
J. Luengo (julianlm@decsai.ugr.es)
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see http://www.gnu.org/licenses/
**********************************************************************/
package keel.Algorithms.Neural_Networks.NNEP_Common.neuralnet;
/**
* <p>
* @author Written by Pedro Antonio Gutierrez Penya, Aaron Ruiz Mora (University of Cordoba) 17/07/2007
* @version 0.1
* @since JDK1.5
* </p>
*/
public class ExpNeuron extends LinkedNeuron {
/**
* <p>
* Represents a exponential neuron (exp transformated Product Unit) of a neural net
* </p>
*/
/////////////////////////////////////////////////////////////////
// --------------------------------------- Serialization constant
/////////////////////////////////////////////////////////////////
/** Generated by Eclipse */
private static final long serialVersionUID = 1649577257047517573L;
/////////////////////////////////////////////////////////////////
// -------------------------------------------------- Constructor
/////////////////////////////////////////////////////////////////
public ExpNeuron() {
super();
}
/////////////////////////////////////////////////////////////////
// -------------------------------- Implementing abstract methods
/////////////////////////////////////////////////////////////////
/**
* <p>
* Init the input of the neuron (0 or 1 depending on the kind of neuron)
* </p>
* @return double Initialized value of the input
*/
protected double initInput(){
return 0.;
}
/**
* <p>
* Input function of the neuron. Update input for each input neuron
* </p>
* @param input Old input
* @param in Output of the input neuron
* @param weight Weight of the link to the input neuron
* @return double Partial input of the input neuron
*/
protected double inputFunction(double input, double in, double weight) {
return input + in*weight;
}
/**
* <p>
* Output function of the neuron
* </p>
* @param input Input of the neuron
* @return double Output of the neuron
*/
protected double outputFunction(double input) {
return Math.exp(input);
}
/////////////////////////////////////////////////////////////////
// ----------------------------------------------- Public methods
/////////////////////////////////////////////////////////////////
/**
* <p>
* Returns a string representation of the ExpNeuron
* </p>
* @return String Representation of the PUNeuron
*/
public String toString(){
StringBuffer sb = new StringBuffer();
double weight;
for(int i=0; i<links.length; i++)
{
if(!links[i].isBroken())
{
weight = links[i].getWeight();
//If it is a bias neuron
if(biased && links[i].getOrigin() == null)
sb.append("* 1^" + weight+" ");
//Else
else
sb.append("* " + links[i].getOrigin().toString()
+ "^" + weight +" ");
}
}
String buffer = sb.toString();
if(buffer.length()!=0){
// Remove the firt "* "
buffer = buffer.substring( buffer.indexOf("*")+2, buffer.length() );
// Remove the last " "
buffer = buffer.substring(0,buffer.length()-1);
}
return buffer;
}
}