cnt.c

GENETIC ALGORITHM FOR NEURAL NETWORKS ON TRANSPUTERS (Source code and Reference)

/* Implementation of 1-norm of a binary vector */
/* out[]=sum(i,in[i]) mod 2^O */

#include "defs.h"
#include "ind.h"
#include "stdnet.h"

/* Parameter Handling */

#define DEFNIN		3
#define DEFNHID		AUTO
#define DEFNOUT		AUTO

#define MAXIN		31
#define MAXHID		255
#define MAXOUT          5

char *StdOptStr() {return "N:M:O:\0";}

char *StdUsage() {return  
  "Network (Counter):\n"
  "-N <no. of input units>:          3\n" 
  "-M <no. of hidden units>:         auto (M)\n" 
  "-O <no. of output units>:         auto (>= ld M)\n\0";}

int Nin=DEFNIN;
int Nhid=DEFNHID;
int Nout=DEFNOUT;

const int grey2dec[16]={0,1,3,2,7,6,4,5,15,14,12,13,8,9,11,10}; 

int handleStdOpt(char opt,char* arg)
{
  switch(opt)
  {
    case 'N': return (Nin	=getint(arg,1,MAXIN))<0;
    case 'M': return (Nhid	=getint(arg,1,MAXHID))<0;
    case 'O': return (Nout	=getint(arg,1,MAXOUT))<0;
  };
  return 1;
}

int initStd()
{
  if(Nhid==AUTO) Nhid=Nin;
  if(Nout==AUTO) Nout=duallog(Nin+1);
  Ntrain=1<<Nin;
  sprintf(StdName,"%d bit Counter (counts 1s in input)",Nin);
  return 0;
}

void initTrain()
{
  int p,z,i;

  for(p=0;p<Ntrain;p++)
  {
    z=0;
    for(i=0;i<Nin;i++)
      z+=TrainIn[p][i]=(float) ((p>>i) & 1);
    for(i=0;i<Nout;i++)
      TrainOut[p][i]=(float) ((z>>i) & 1);  
  };
}