percept.cpp

感知器的VC实现#include "percept.h" #include "stdio.h" #include "stdlib.h"

//percept.cpp   V. Rao, H. Rao
//Perceptron model

#include "percept.h"
#include "stdio.h"
#include "stdlib.h"

ineuron::ineuron(float j)
{
weight= j;
}

float ineuron::act(float x)
{
float a;

a = x*weight;

return a;
}

void oneuron::actvtion(float *inputv, ineuron *nrn)
{
int i;
activation = 0;

for(i=0;i<4;i++)
     {
     cout<<"\nweight for neuron "<<i+1<<" is       "<<nrn[i].weight;
     nrn[i].activation = nrn[i].act(inputv[i]);
     cout<<"           activation is      "<<nrn[i].activation;
     activation += nrn[i].activation;
     }
cout<<"\n\nactivation is  "<<activation<<"\n";
}

int oneuron::outvalue(float j)
{
if(activation>=j)
     {
     cout<<"\nthe output neuron activation \
exceeds the threshold value of "<<j<<"\n";
     output = 1;
     }
else
     {
     cout<<"\nthe output neuron activation \
is smaller than the threshold value of "<<j<<"\n";
     output = 0;
     }

cout<<" output value is "<< output;
return (output);
}

network::network(float a,float b,float c,float d)
{
nrn[0] = ineuron(a) ;
nrn[1] = ineuron(b) ;
nrn[2] = ineuron(c) ;
nrn[3] = ineuron(d) ;
onrn = oneuron();
onrn.activation = 0;
onrn.output = 0;
}
void main (int argc, char * argv[])
{

float inputv1[]= {1.95,0.27,0.69,1.25};
float wtv1[]= {2,3,3,2}, wtv2[]= {3,0,6,2};
FILE * wfile, * infile;
int num=0, vecnum=0, i;
float threshold = 7.0;

if (argc < 2)
     {
     cerr << "Usage: percept Weightfile Inputfile";
     exit(1);
     }
// open  files

wfile= fopen(argv[1], "r");
infile= fopen(argv[2], "r");

if ((wfile == NULL) || (infile == NULL))
     {
     cout << " Can't open a file\n";
     exit(1);
     }

cout<<"\nTHIS PROGRAM IS FOR A PERCEPTRON NETWORK WITH AN INPUT LAYER OF";
cout<<"\n4 NEURONS, EACH CONNECTED TO THE OUTPUT NEURON.\n";
cout<<"\nTHIS EXAMPLE TAKES REAL NUMBERS AS INPUT SIGNALS\n";

//create the network by calling its constructor.
//the constructor calls neuron constructor as many times as the number of
//neurons in input layer of the network.

cout<<"please enter the number of weights/vectors \n";
cin >> vecnum;

for (i=1;i<=vecnum;i++)
     {
     fscanf(wfile,"%f %f %f %f\n", &wtv1[0],&wtv1[1],&wtv1[2],&wtv1[3]);
     network h1(wtv1[0],wtv1[1],wtv1[2],wtv1[3]);
     fscanf(infile,"%f %f %f %f \n",
     &inputv1[0],&inputv1[1],&inputv1[2],&inputv1[3]);
     cout<<"this is vector # " << i << "\n";
     cout << "please enter a threshold value, eg 7.0\n";
     cin >> threshold;
     h1.onrn.actvtion(inputv1, h1.nrn);
     h1.onrn.outvalue(threshold);
     cout<<"\n\n";
     }

fclose(wfile);
fclose(infile);
}