layer.java

用Java实现的多层BP神经网络

/*  AI ANN Backpropagation
    Copyright (C) 2002-2003  Wim Gillis <[e-mail]>
    http://sourceforge.net/projects/crap

    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.

    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 (see COPYING); if not, check out 
    http://www.gnu.org/licenses/gpl.html
    or write to the Free Software Foundation, 
    Inc., 59 Temple Place, Suite 330, Boston, 
    MA  02111-1307  USA
*/

package cx.ma.ai.ann.backprop;

import java.io.Serializable;

public class Layer implements Serializable{    
    private Neuron[] neurons;
    
    public Layer(int noOfNeurons, Layer previousLayer, double weightDefaultValue, int activationType) {
        neurons = new Neuron[noOfNeurons]; 
        for (int i = 0; i < neurons.length; ++i) {
            if (previousLayer != null) 
                neurons[i] = new Neuron(previousLayer.getNoOfNeurons(), weightDefaultValue, activationType);   
            else    
                neurons[i] = new Neuron(0, 0, activationType);
        }
    }
    
    public Layer(Layer layer) {
        neurons = new Neuron[layer.getNoOfNeurons()];
        for (int i = 0; i < layer.getNoOfNeurons(); ++i) {
            neurons[i] = new Neuron (layer.getNeuron (i));
        }
    }
    
    public int getNoOfNeurons(){
        return neurons.length;
    }
    
    public Neuron getNeuron(int index){
        return neurons[index];
    }
    
    public void calculateNets(Layer previousLayer){
        for (int i = 0; i < neurons.length; ++i)
            neurons[i].calculateNet (previousLayer);
    }
    
    public String toString(){
        String out = "";
        for (int i = 0; i < neurons.length; ++i)
            out += "\t\tNeuron " + i + "\n" + neurons[i].toString() + "\n";
        return out;
    }
}