/*

* mlp-java, Copyright (C) 2012 Davide Gessa

*

* 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 2 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 multilayersperceptronlib.test;

import multilayersperceptronlib.MultiLayerPerceptron;

import multilayersperceptronlib.transferfunctions.HyperbolicTransfer;

public class MassiveTest

{

/**

* @param args

*/

public static void main(String[] args)

{

int[] layers = new int[]{ 16*16, 16*16/2, 40 };

MultiLayerPerceptron net = new MultiLayerPerceptron(layers, 0.6, new HyperbolicTransfer());

/* Learning */

for(int i = 0; i < 100000; i++)

{

double[] inputs = new double[16*16];

double[] output = new double[40];

double error;

for(int j = 0; j < inputs.length; j++)

inputs[j] = 0;

error = net.backPropagate(inputs, output);

System.out.println("Error at step "+i+" is "+error);

}

System.out.println("Learning completed!");

}

}