00001 /*!@file Neuro/WinnerTakeAllStdOptim.H Optimized version of WinnerTakeAllStd */ 00002 00003 // //////////////////////////////////////////////////////////////////// // 00004 // The iLab Neuromorphic Vision C++ Toolkit - Copyright (C) 2000-2005 // 00005 // by the University of Southern California (USC) and the iLab at USC. // 00006 // See http://iLab.usc.edu for information about this project. // 00007 // //////////////////////////////////////////////////////////////////// // 00008 // Major portions of the iLab Neuromorphic Vision Toolkit are protected // 00009 // under the U.S. patent ``Computation of Intrinsic Perceptual Saliency // 00010 // in Visual Environments, and Applications'' by Christof Koch and // 00011 // Laurent Itti, California Institute of Technology, 2001 (patent // 00012 // pending; application number 09/912,225 filed July 23, 2001; see // 00013 // http://pair.uspto.gov/cgi-bin/final/home.pl for current status). // 00014 // //////////////////////////////////////////////////////////////////// // 00015 // This file is part of the iLab Neuromorphic Vision C++ Toolkit. // 00016 // // 00017 // The iLab Neuromorphic Vision C++ Toolkit is free software; you can // 00018 // redistribute it and/or modify it under the terms of the GNU General // 00019 // Public License as published by the Free Software Foundation; either // 00020 // version 2 of the License, or (at your option) any later version. // 00021 // // 00022 // The iLab Neuromorphic Vision C++ Toolkit is distributed in the hope // 00023 // that it will be useful, but WITHOUT ANY WARRANTY; without even the // 00024 // implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR // 00025 // PURPOSE. See the GNU General Public License for more details. // 00026 // // 00027 // You should have received a copy of the GNU General Public License // 00028 // along with the iLab Neuromorphic Vision C++ Toolkit; if not, write // 00029 // to the Free Software Foundation, Inc., 59 Temple Place, Suite 330, // 00030 // Boston, MA 02111-1307 USA. // 00031 // //////////////////////////////////////////////////////////////////// // 00032 // 00033 // Primary maintainer for this file: Rob Peters <rjpeters at usc dot edu> 00034 // $HeadURL: svn://isvn.usc.edu/software/invt/trunk/saliency/src/Neuro/WinnerTakeAllStdOptim.H $ 00035 // $Id: WinnerTakeAllStdOptim.H 10670 2009-01-23 19:42:06Z itti $ 00036 // 00037 00038 #ifndef NEURO_WINNERTAKEALLSTDOPTIM_H_DEFINED 00039 #define NEURO_WINNERTAKEALLSTDOPTIM_H_DEFINED 00040 00041 #include "Neuro/WinnerTakeAll.H" 00042 00043 // ###################################################################### 00044 //! Optimized version of the standard winner-take-all 00045 // ###################################################################### 00046 /*! This is an optimized version of WinnerTakeAllStd which should give 00047 the same results, but with better CPU efficiency. */ 00048 class WinnerTakeAllStdOptim : public WinnerTakeAllAdapter 00049 { 00050 public: 00051 //! Ininitialized constructor 00052 /*! The WTA will be resized and initialized the first time input() is 00053 called */ 00054 WinnerTakeAllStdOptim(OptionManager& mgr, 00055 const std::string& descrName = "Optimized Winner-Take-All Std", 00056 const std::string& tagName = "WinnerTakeAllStdOptim"); 00057 00058 //! Destructor 00059 virtual ~WinnerTakeAllStdOptim(); 00060 00061 //! Reset to initial state just after construction 00062 virtual void reset1(); 00063 00064 protected: 00065 //! Set new input currents for all neurons 00066 /*! This will initialize and resize the network if the network is 00067 currently uninitialized (e.g., just after construction or reset()). */ 00068 virtual void input(const Image<float>& in); 00069 00070 //! Return all our membrane potential voltages as an Image<float> 00071 virtual Image<float> getV() const; 00072 00073 //! Integrate inputs until time t (in s) and update membrane potentials 00074 virtual void integrate(const SimTime& t, Point2D<int>& winner); 00075 00076 //! Turn saccadic suppression on/off 00077 virtual void saccadicSuppression(const bool on); 00078 00079 //! Turn blink suppression on/off 00080 virtual void blinkSuppression(const bool on); 00081 00082 private: 00083 00084 const SimTime itsTimeStep;// time step to use for difference equations (in s) 00085 float itsGe; // excitatory conductance in Siemens 00086 float itsGi; // inhibitory conductance in Siemens 00087 const float itsEl; // driving potential for leak part, in Volts 00088 const float itsEe; // driving potential for excitatory part, in Volts 00089 const float itsEi; // driving potential for inhibitory part, in Volts 00090 const float itsC; // capacitance in Farads 00091 const float itsVth; // spike threshold voltage in Volts 00092 Image<float> itsV; 00093 SimTime itsT; // time of last integration 00094 const float itsGleak; // leak conductance in Siemens 00095 const float itsGinh; // in Siemens 00096 const float itsGinput; // in Siemens 00097 00098 // GIN == Global Inhibitory Neuron 00099 const float itsGIN_Gl; // GIN leak conductance in Siemens 00100 float itsGIN_Ge; // GIN excitatory conductance in Siemens 00101 const float itsGIN_El; // GIN driving potential for leak part, in Volts 00102 const float itsGIN_Ee; // GIN driving potential for excitatory part, in V 00103 const float itsGIN_Ei; // GIN driving potential for inhibitory part, in V 00104 const float itsGIN_C; // GIN capacitance in Farads 00105 const float itsGIN_Vth; // GIN spike threshold voltage in Volts 00106 float itsGIN_V; // GIN membrane potential in Volts 00107 Image<float> itsInputCopy; 00108 00109 void inhibit(); // inhibit the whole layer 00110 00111 class EvolveJob; 00112 }; 00113 00114 // ###################################################################### 00115 /* So things look consistent in everyone's emacs... */ 00116 /* Local Variables: */ 00117 /* mode: c++ */ 00118 /* indent-tabs-mode: nil */ 00119 /* End: */ 00120 00121 #endif // NEURO_WINNERTAKEALLSTDOPTIM_H_DEFINED
1.6.3