elman.h

Go to the documentation of this file.

/***************************************************************************
 *   Copyright (C) 2005 by Robot Group Leipzig                             *
 *    martius@informatik.uni-leipzig.de                                    *
 *    fhesse@informatik.uni-leipzig.de                                     *
 *    der@informatik.uni-leipzig.de                                        *
 *                                                                         *
 *   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.,                                       *
 *   59 Temple Place - Suite 330, Boston, MA  02111-1307, USA.             *
 ***************************************************************************
 *                                                                         *
 *  DESCRIPTION                                                            *
 *                                                                         *
 *   $Log: elman.h,v $
 *   Revision 1.2  2006/11/29 16:22:43  martius
 *   name is a variable of configurable and is used as such
 *
 *   Revision 1.1  2006/07/27 15:22:31  martius
 *   activations stored (processing must preceed learning and reponse calculation)
 *
 *
 *                                                                 *
 ***************************************************************************/
#ifndef __ELMAN_H
#define __ELMAN_H

#include <vector>

#include "multilayerffnn.h"

/** Multilayer Neural Network with context neurons (after Elman)
Example of 2 hidden layer network
   O O O
   | | |
   H H H ----->-----+ 1:1 fixed connections (time delayed)
   | | |\-<-<  __   |
   | | | \ \ \/  |l |  l = lambda -> recurrent connection
   | | |  C C C<-+  | 
   | | |  ^-^-^--<--+
   H H H ----->-----+ 1:1 fixed connections (time delayed)
   | | |\-<-<  __   |
   | | | \ \ \/  |l |  l = lambda -> recurrent connection
   I I I  C C C<-+  | 
          ^-^-^--<--+
 */
class Elman : public MultiLayerFFNN {
public: 
  /**
     @param eps learning rate
     @param layers Layer description (the input layer is not specified (always linear))
     @param lambda self-recurrent feedback strength of context neurons
  */
  Elman(double eps, const std::vector<Layer>& layers, double lambda)
    : MultiLayerFFNN(eps,layers), lambda(lambda) { 
    
    initialised = false;  
  }
  virtual ~Elman(){ }

  /// initialisation of the network with the given number of input and output units
  virtual void init(unsigned int inputDim, unsigned  int outputDim, double unit_map = 0.0); 

  /** passive processing of the input 
      (this will be different for every input, since it is a recurrent network)
  */
  virtual const matrix::Matrix process (const matrix::Matrix& input); 

  /// performs learning and returns the network output before learning
  virtual const matrix::Matrix learn (const matrix::Matrix& input, 
                                      const matrix::Matrix& nom_output, 
                                      double learnRateFactor = 1);

  /** \see InvertableModel::response
   */
  /* Is implemented in multilayerfnn
     virtual const matrix::Matrix response(const matrix::Matrix& input) const;     
   */
  
  /**************  STOREABLE **********************************/
  /// stores the layer binary into file stream
  bool store(FILE* f) const;
  /// restores the layer binary from file stream
  bool restore(FILE* f);


  /************** CONFIGURABLE INTERFACE ************************/
  virtual paramkey getName() const {
    return std::string("elmanNN");
  }

protected:
  std::vector<matrix::Matrix> contextweights;
  std::vector<matrix::Matrix> contexts;
  double lambda;

};

#endif

---