nnwhere.c

基于MATLAB完成的神经网络源程序 大家

/*--------------------------------------------------------------------------*
 * Gregory Stevens                                                   7/5/93 *
 *                               NNWHERE.C                                  *
 *                                                                          *
 *   This is a program to be used with the nn*.c series for implementing    *
 * the "what" feature detector algorithm described in the paper called      *
 * "Why are What and Where Processed By Separate Cortical Visual Systems?"  *
 * by J.G. Rueckl and Kyle R. Cave.  The following constant settings must   *
 * be made:                                                                 *
 *      NNPARAMS.C : INPUT_LAYER_SIZE   25    (the retina: 5x5)             *
 *                   OUTPUT_LAYER_SIZE  9     (9 possible positions)        *
 *                   NUM_HIDDEN_LAYERS  0                                   *
 *                   HL_SIZE_1          0     (this can be changed)         *
 *                                                                          *
 *      NNINPUTS.C : NUM_PATTERNS  72         (8 patterns in 9 positions)++ *
 *                                                                          *
 *      NNSTRUCT.C : InitNet()  ...should set output nodes as logistic...   *
 *                                                                          *
 *      NNBKPROP.C : EPSILON 0.25  (recommended...this is what I used)      *
 *                                                                          *
 *--------------------------------------------------------------------------*/
#include "nnbkprop.c"                /* to chain it to the nn*.c utilities  */
#include <math.h>                    /* for the exp() for logistic units    */

#define NUM_ITS 100                  /* iterations before it stops          */

/*  MAIN PROGRAM  */
void main()
{
  int Pattern;                         /* for looping through patterns   */
  int Layer;                           /* for looping through layers     */
  int LCV;                             /* for looping training sets      */
  NNETtype Net;
  PATTERNtype InPatterns, OutPattern;

  Net = InitNet( NUMNODES );            /* initializes the network        */
  InPatterns = InitInPatterns(0);       /* loads input patterns from file */
  OutPattern = InitOutPatterns();       /* loads output patterns from file*/

  for (LCV=0; (LCV < NUM_ITS); ++LCV)   /* loop through a training set    */
    {
      for (Pattern=0; (Pattern<NUM_PATTERNS); ++Pattern)
         {
            /* FORWARD PROPAGATION */
            Net = UpDateInputAct( InPatterns, Pattern, Net );
            for (Layer=1; (Layer<NUMLAYERS); ++Layer)
              {
                 Net = UpDateLayerAct( Net, Layer );
              }

            /* OUTPUT PRINTS */
            printf( "Pat: %d  ", Pattern );
            printf( "Itr: %d", LCV );
            printf( "\n" );
            DisplayLayer( Net, 0, 5 ); /* display input layer  */
            printf( "\n" );
            DisplayLayer( Net, 1, 9 ); /* display output layer */
            printf( "\n" );
            if (LCV>90) getc(stdin);

            /* BACKWARD PROPAGATION */
            Net = UpDateWeightandThresh( Net, OutPattern, Pattern );
         }
    }
}