CompLayer.H

Go to the documentation of this file.
00001 /*!@file ModelNeuron/CompLayer.H Class declarations for structure that
00002 consists of an Gaussian excitatory layer which projects to an inhibitory layer,
00003 which projects in a gaussian pattern pack to the excitatory layer. Inspired by
00004 the layout of the mamillian SC. */
00005 
00006 // //////////////////////////////////////////////////////////////////// //
00007 // The iLab Neuromorphic Vision C++ Toolkit - Copyright (C) 2001 by the //
00008 // University of Southern California (USC) and the iLab at USC.         //
00009 // See http://iLab.usc.edu for information about this project.          //
00010 // //////////////////////////////////////////////////////////////////// //
00011 // Major portions of the iLab Neuromorphic Vision Toolkit are protected //
00012 // under the U.S. patent ``Computation of Intrinsic Perceptual Saliency //
00013 // in Visual Environments, and Applications'' by Christof Koch and      //
00014 // Laurent Itti, California Institute of Technology, 2001 (patent       //
00015 // pending; application number 09/912,225 filed July 23, 2001; see      //
00016 // http://pair.uspto.gov/cgi-bin/final/home.pl for current status).     //
00017 // //////////////////////////////////////////////////////////////////// //
00018 // This file is part of the iLab Neuromorphic Vision C++ Toolkit.       //
00019 //                                                                      //
00020 // The iLab Neuromorphic Vision C++ Toolkit is free software; you can   //
00021 // redistribute it and/or modify it under the terms of the GNU General  //
00022 // Public License as published by the Free Software Foundation; either  //
00023 // version 2 of the License, or (at your option) any later version.     //
00024 //                                                                      //
00025 // The iLab Neuromorphic Vision C++ Toolkit is distributed in the hope  //
00026 // that it will be useful, but WITHOUT ANY WARRANTY; without even the   //
00027 // implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR      //
00028 // PURPOSE.  See the GNU General Public License for more details.       //
00029 //                                                                      //
00030 // You should have received a copy of the GNU General Public License    //
00031 // along with the iLab Neuromorphic Vision C++ Toolkit; if not, write   //
00032 // to the Free Software Foundation, Inc., 59 Temple Place, Suite 330,   //
00033 // Boston, MA 02111-1307 USA.                                           //
00034 // //////////////////////////////////////////////////////////////////// //
00035 //
00036 // Primary maintainer for this file: David Berg <dberg@usc.edu>
00037 // $HeadURL: svn://isvn.usc.edu:/software/invt/trunk/saliency/src/ModelNeuron/CompLayer.H $
00038 
00039 #ifndef  NEURALMODEL_COMPLAYER_H_DEFINED
00040 #define  NEURALMODEL_COMPLAYER_H_DEFINED
00041 
00042 #include "ModelNeuron/Structure.H"
00043 #include "ModelNeuron/Layer.H"
00044 #include "ModelNeuron/Weights.H"
00045 
00046 // ######################################################################
00047 //  CompLayer
00048 //  ######################################################################
00049 // A class representing a single lamina containing excitatory and
00050 // inhibitory neurons. A network containing interacting excitatory and
00051 // inhhibitory units where an excitatory layer (input layer) has local
00052 // recurrent excitation. Each unit in the exciatory layer connects
00053 // directly to a single unit in the inhibitory layer. The inhibitory
00054 // units connect in a gaussian pattern back to the excitatory
00055 // network. A variety of behaviors can be obtained such as bumbs,
00056 // waves, weak winner take all selection etc....
00057 //
00058 // It is hypothesized that each layer of the primate colliculus (Sgs,
00059 // Sgi) supperior colliculus is organized in such a way, with
00060 // different sized excitation and inhibition regions.
00061 //
00062 // Computational framework inspired by work from SI Amari. See SC
00063 // class for citations on inspiration for the construction of a model
00064 // Sgs and Sgi, and interlaminar connectivity.
00065 //  ######################################################################
00066 template <class EUnit, class IUnit>
00067 struct CompLayer : public Structure<SimLayer*>
00068 {
00069   //! constructor
00070   CompLayer(const double& excite_std, const double& inhibit_std,
00071             const double& excite_w, const double& feedforward, const double& feedback,
00072             const BorderPolicy bp, const SimTime& timestep, 
00073             const uint width, const uint height, const std::string name = "", const std::string units = "")
00074     : Structure<SimLayer*>(timestep, width, height, name, units),
00075       itsW(inhibit_std, feedback, false, bp), itsFF(feedforward) 
00076   { 
00077     Layer<EUnit, WeightsBinomial> itsE(excite_std, excite_w, true, bp, timestep, width, height, "Excitatory");
00078     Layer<IUnit, WeightsEmpty> itsI(timestep, width, height, "Inhibitory");
00079     addSub(itsE); 
00080     addSub(itsI);
00081     setDefaultIO(0,0);
00082   }
00083   
00084   //default copy and assignment OK
00085   
00086   //!destructor 
00087   virtual ~CompLayer() { };  
00088   
00089   //set the modules
00090   void setModules(const SimUnit& excite_module, const SimUnit& inhibit_module)
00091   {
00092     editSub(0).setModule(excite_module);
00093     editSub(1).setModule(inhibit_module);
00094   }
00095   
00096   //!get the current display output 
00097   Image<double> getDisplayOutput(const int pos = -1) const
00098   {
00099     if (pos < 0)
00100       {
00101         Image<double> e = getSub(0).getDisplayOutput();
00102         const Image<double> i = getSub(1).getDisplayOutput();
00103         e -= i;
00104         return e;
00105       }
00106     else
00107       return getSub(pos).getDisplayOutput();
00108   }
00109 
00110   //!cone the unit
00111   CompLayer<EUnit, IUnit>* clone() const {return new CompLayer<EUnit,IUnit>(*this); }
00112   
00113 private:
00114   //!do our class specific interactions
00115   void interact()
00116   {
00117 
00118     //excite->inhibit
00119     Image<double> e = getSub(0).getOutput();
00120     e *= itsFF;
00121     input(e, 1);
00122     
00123     //inhbit->excite
00124     const Image<double> i = getSub(1).getOutput();
00125     const Image<double> iw = itsW.compute(i);
00126     input(iw, 0);
00127   }
00128 
00129   WeightsBinomial itsW;
00130   double itsFF;
00131 };
00132 
00133 #endif  
00134 // ######################################################################
00135 /* So things look consistent in everyone's emacs... */
00136 /* Local Variables: */
00137 /* indent-tabs-mode: nil */
00138 /* End: */
Generated on Sun May 8 08:41:01 2011 for iLab Neuromorphic Vision Toolkit by  doxygen 1.6.3