simple_sigmoid.cpp

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/*
    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 sigmoid network with no specific function.*/

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

int main(){
	SIGMOID *hidden1 = new SIGMOID( );
	hidden1->definef( 2, 2, -2.0, 3.0, -2.0, 3.0 );
	derived.LoadVectorf( hidden1->weight, 2, 2.0, 2.0 );
	
	SIGMOID *hidden2 = new SIGMOID( );
	hidden2->definef( 2, 2, -2.0, 2.0, -4.0, 2.0 );
	derived.LoadVectorf( hidden2->weight, 2, 3.0, -2.0 );
	
	SIGMOID *output = new SIGMOID( );
	output->definef( 2, 1, 3.0, 1.0 );
	derived.LoadVectorf( output->weight, 1, -2.0 );

	layer<float> *ppHidden1 = hidden1;
	layer<float> *ppHidden2 = hidden2;
	layer<float> *ppOutput  = output;
	
	derived.Insert( &ppHidden1, &ppHidden2 );
	derived.Insert( &ppHidden2, &ppOutput );
	
	nn_utility_functions<float>::VECTOR input, FINAL, target;
	derived.LoadVectorf( input, 2, 0.1, 0.9 );
	derived.LoadVectorf( target, 1, 0.9 );
	
	hidden1->FeedForward( input, FINAL );
	cout << "Feedforward sigmoid fires: "; derived.PrintVector( FINAL, 1 );
	
	output->BackPropagate( input, target, 0.3, 1 );
	
	cout << "After backpropagation the resulting weights are: ";
	derived.DisplayLAYER( &ppHidden1 );
	
	cout << '\n';
	return 0;
}