include/backpropagationalgo.h

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/********************************************************************************
 *  Neural Network Framework.                                                   *
 *  Copyright (C) 2005-2008 Gianluca Massera <emmegian@yahoo.it>                *
 *                                                                              *
 *  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, write to the Free Software                 *
 *  Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA  02110-1301  USA  *
 ********************************************************************************/

#ifndef BACKPROPAGATIONALGO_H
#define BACKPROPAGATIONALGO_H

#include "types.h"
#include "learningalgorithm.h"
#include <map>

namespace nnfw {

class AbstractModifier;

class NNFW_API BackPropagationAlgo : public LearningAlgorithm {
public:

    BackPropagationAlgo( BaseNeuralNet *n_n, UpdatableVec update_order, Real l_r = 0.1f );

    ~BackPropagationAlgo( );



    void setTeachingInput( Cluster* output, const RealVec& ti );

    virtual void learn();

    virtual void learn( const Pattern& );

    virtual Real calculateMSE( const Pattern& );

    void setRate( Real newrate ) {
        learn_rate = newrate;
    };

    Real rate() {
        return learn_rate;
    };

    void setMomentum( Real newmom ) {
        momentumv = newmom;
    };

    Real momentum() {
        return momentumv;
    };

    void enableMomentum();

    void disableMomentum() {
        useMomentum = false;
    };

    const RealVec& getError( Cluster* );

private:
    Real learn_rate;
    Real momentumv;
    Real useMomentum;
    UpdatableVec update_order;

    class NNFW_API cluster_deltas {
    public:
        Cluster* cluster;
        AbstractModifier* modcluster;
        bool isOutput;
        RealVec deltas_outputs;
        RealVec deltas_inputs;
        RealVec last_deltas_inputs;
        LinkerVec incoming_linkers_vec;
        VectorData<AbstractModifier*> incoming_modlinkers;
        VectorData<RealVec> incoming_last_outputs;
    };
    std::map<Cluster*, int> mapIndex;
    VectorData<cluster_deltas> cluster_deltas_vec;
    // --- propagate delta through the net
    void propagDeltas();
    // --- add a Cluster into the structures above
    void addCluster( Cluster*, bool );
    // --- add a Linker into the structures above
    void addLinker( Linker* );

};

}

#endif

Copyright © 2005-2008 G. Massera

Contact: emmegian (at) yahoo (dot) it

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