nnsim2.c

基于MATLAB完成的神经网络源程序 大家

/*--------------------------------------------------------------------------*
 * Gregory Stevens                                                   7/1/93 *
 *                                NNSIM2.C                                  *
 *    (Generalized Simulator: UnSupervised,Feed Forward,Hebbian Learning)   *
 *                                                                          *
 *   This is a generalized simulator for a supervised feed-forward neural   *
 * with back-propagation.  It uses the nn*.c series.                        *
 * For this file, the following parameters in the following files should be *
 * set to comply with the input file and desired net configuration:         *
 *      NNPARAMS.C : INPUT_LAYER_SIZE                                       *
 *                   OUTPUT_LAYER_SIZE                                      *
 *                   NUM_HIDDEN_LAYERS 0                                    *
 *                   HL_SIZE_#         0                                    *
 *                                                                          *
 *      NNINPUTS.C : NUM_PATTERNS                                           *
 *                                                                          *
 *      NNSTRUCT.C : InitNet()   (output nodes should be linear)            *
 *                                                                          *
 *      NNHEBBLN.C : EPSILON 0.05  (recommended...this is what I used)      *
 *                                                                          *
 *   There should be 2 data files: nninputs.dat, nnintest.dat               *
 * The later is only necessary if IN_TEST is set to 1, and is to test the   *
 * net on novel inputs.                                                     *
 *                                                                          *
 *--------------------------------------------------------------------------*/
#include "nncompet.c"                /* to chain it to the nn*.c utilities  */

#define NUM_ITS 100                  /* iterations before it stops training */
#define IN_TEST 1

void main()
{
  int Pattern;                          /* for looping through patterns   */
  int Layer;                            /* for looping through layers     */
  int LCV;                              /* for looping training sets      */
  NNETtype Net;                         /* for the network itself         */
  PATTERNtype InPatterns;               /* for the training patterns      */

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

  printf("\n\n\n\n\n");                 /* gets screen ready for output   */

  printf( "BEGINNING TRAINING:\n\n" );

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

              /* for Hebbian, non-competative, comment out the next line: */
              Net = AllOrNoneLayerActs( Net, Layer );
             }

            /* OUTPUT PRINTS */
            /*    NOTE: The last number in DisplayLayer() will need to be */
            /*          adjusted to format different size input layers.   */

            DisplayLayer( Net, 0, 4 );             /* display input layer */
            printf( "   " );
            DisplayLayer( Net, (NUMLAYERS-1), 4 ); /* display output layer*/
            printf( "\n" );                        /* new line            */

            /* LEARNING RULE */
            Net = UpDateWeightandThresh( Net );
         }

      printf( "\n\n" );                            /* prepare for next set*/

      if ( LCV > (NUM_ITS-10) )
        {
           getc(stdin);           /* pause inbetween training epochs */
        }
    }

  if (IN_TEST==1)
    {
      InPatterns = InitInPatterns(1);          /* Loads test input patterns */

      printf( "BEGINNING PATTERN TESTING:\n\n" );

      for (Pattern=0; (Pattern<NUM_PATTERNS); ++Pattern)
         {
            Net = UpDateInputAct( InPatterns, Pattern, Net );
            for (Layer=1; (Layer<NUMLAYERS); ++Layer )
             {
              Net = UpDateLayerAct( Net, Layer );

              /* for Hebbian, non-competative, comment out the next line: */
              Net = AllOrNoneLayerActs( Net, Layer );
             }

            /* OUTPUT PRINTS */
            /*    NOTE: The last number in DisplayLayer() will need to be */
            /*          adjusted to format different size input layers.   */

            DisplayLayer( Net, 0, 4 );             /* display input layer */
            printf( "   " );
            DisplayLayer( Net, 1, 5 );             /* display output layer*/
            printf( "\n" );                        /* new line            */
         }

      getc(stdin);
    }
}