libradialfunctions.h

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/********************************************************************************
 *  Neural Network Framework.                                                   *
 *  Copyright (C) 2005-2011 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 LIBRADIALFUNCTIONS_H
#define LIBRADIALFUNCTIONS_H

#include "nnfwconfig.h"

#include "outputfunction.h"

namespace farsa {

class FARSA_NNFW_API GaussFunction : public OutputFunction {
public:
    GaussFunction( double centre = 0.0, double variance = 1.0, double maxvaule = 1.0 );
    virtual ~GaussFunction() { /* Nothing to do */ };
    bool setVariance( double v );
    double variance();
    virtual void apply( DoubleVector& inputs, DoubleVector& outputs );
    virtual bool derivate( const DoubleVector& x, const DoubleVector& y, DoubleVector& d ) const;
    virtual void configure(ConfigurationParameters& params, QString prefix);
    virtual void save(ConfigurationParameters& params, QString prefix);
    double centre;
    double max;
private:
    // variance
    double variancev;
    // minus squared-variance
    double msqrvar;
};

}

#endif