binomial.cpp

BP神经网络算法的VC＋源码

/*
    nn-utility (Provides neural networking utilities for c++ programmers)
    Copyright (C) 2003 Panayiotis Thomakos

    This library is free software; you can redistribute it and/or
    modify it under the terms of the GNU Lesser General Public
    License as published by the Free Software Foundation; either
    version 2.1 of the License, or (at your option) any later version.

    This library 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
    Lesser General Public License for more details.
*/
//To contact the author send an email to [e-mail]

/*Demonstrates an operational binomial network that performs the XOR function.*/

#include <nn-utility.h>
using namespace nn_utility;
nn_utility_functions<float> derived;

int main(){
	//first layer is a binomial layer
	BINOMIAL *hidden1 = new BINOMIAL();
	//define it's matrix
	hidden1->definef( 2,2, -1.0, -1.0, -1.0, -1.0);
	//define it's bias weights
		derived.LoadVectorf( hidden1->weight, 2, 1.5, 0.5 );

	//second layer is a binomial layer
	BINOMIAL *output = new BINOMIAL();
	//define it's matrix
	output->definef( 2,1, 1.0, -1.0 );
	//define it's weights
		derived.LoadVectorf( output->weight, 1, -0.5 );

	//create buffers for the layers
	layer<float> *ppHidden1 = hidden1;
	layer<float> *ppOutput = output;
		
	//connect the two layers using their buffers
	derived.Insert( &ppHidden1, &ppOutput );
	
	//create an input and output VECTOR
	nn_utility_functions<float>::VECTOR input,  FINAL;

	//next few lines load the input vector, fire to the network, and present an output
	//for 1,0  0,1  1,1  and  0,0
	
	derived.LoadVectorf( input, 2, 1.0, 0.0 );
	hidden1->FeedForward( input, FINAL );
	cout << "XOR Binomial Network Presented with : 1,0. Ouptut: "; derived.PrintVector( FINAL, 1 );

	derived.LoadVectorf( input, 2, 0.0, 1.0 );
	hidden1->FeedForward( input, FINAL );
	cout << "XOR Binomial Network Presented with : 0,1. Ouptut: "; derived.PrintVector( FINAL, 1 );

	derived.LoadVectorf( input, 2, 1.0, 1.0 );
	hidden1->FeedForward( input, FINAL );
	cout << "XOR Binomial Network Presented with : 1,1. Ouptut: "; derived.PrintVector( FINAL, 1 );

	derived.LoadVectorf( input, 2, 0.0, 0.0 );
	hidden1->FeedForward( input, FINAL );
	cout << "XOR Binomial Network Presented with : 0,0. Ouptut: "; derived.PrintVector( FINAL, 1 );

	cout << '\n';
	return 0;
}