ly.cpp

基于VC开发的一个神经网络源程序,与大家共享

#include <stdio.h>
#include <math.h>
#include <string.h>

void feedforward(int layernum,int n[],int k,double y[],double w[],double b[]);
void calcdelta(int layernum,int n[],int k,double d[],double y[],double w[],double delta[]);
void update(int layernum,int n[],int k,double y[],double delta[],double miu,double w[],double b[]);
void update(int layernum,int n[],int k,double y[],double delta[],double miu,double w[],double b[]);
static double f(double x);
static double fd(double x);
void init(int layernum,int n[],int k,double w[],double b[]);
void input(int n[],double y[]);
void output(int layernum,int n[],int k,double y[]);
void saveparameter(int layernum,int n[],int k,double w[],double b[]);
void readparameter(int *layernum,int n[],int *k,double w[],double b[]);


//主函数
void main(void)
{
	int i,j=0,k,l,l1,p,choice,layernum,iternum,sampnum;
	double miu,eps,e,ep;
	int n[10];
	char fname[14];
	char chyn[1];
	static double w[500],b[100],y[100],d[100],delta[100];
	FILE *fp;;
    puts("1--Training,2--Output");
	scanf("%d",&choice);

	if(choice==1)
	{
		puts("Input name of training sample data file");
		scanf("%s",fname);
        sampnum=4;
		miu=0.5;
		eps=0.0001;
		puts("Input the number of training(iteration)");
		scanf("%d",&iternum);
		puts("Input layer number of 数据");
		scanf("%d",&layernum);
		puts("Input node number of each layer");
		
		  for(l=0;l<layernum;l++)
		  {
			  printf("N(%d)=",l);
			  scanf("%d",&n[l]);
			  printf("\n");
			}
		  k=n[0];

		 for(l=1;l<layernum;l++)//layernum=3
		  {
			  if(k<n[l]) {
				k=n[l];
			  }
		  }
  
	  init(layernum,n,k,w,b);

	for(p=1;p<=iternum;p++)
	  {
          e=0.0;
		if((fp=fopen(fname,"r"))==NULL){
			
				puts("\ncannot open the sample file");
			
				return;
			}

			ep=0.0;
    		for(i=0;i<sampnum;i++)
    		{
    		
				for(j=0;j<n[0];j++){
					fscanf(fp,"%lf,",&y[j]);
				}
    		
				for(j=0;j<n[layernum-1];j++){
					fscanf(fp,"%lf,",&d[j]);
				}

				feedforward(layernum,n,k,y,w,b);
				calcdelta(layernum,n,k,d,y,w,delta);
				update(layernum,n,k,y,delta,miu,w,b);
    		
				for(l=0;l<n[layernum-1];l++) {   
					l1=layernum-1; 
                    ep += (d[l]-y[(l1)*k+l])*(d[l]-y[(l1)*k+l]);}
					e=e+ep/2.0;
    		
			}
           fclose(fp);
      		if(e<eps)
		{
			printf("\nActual training number=%d\n other=%lf",p,eps);
			printf("\nThe overall error=%lf\n",e);
			break;
		}
 
	  }
	  
	  
	  printf("\nDo you want to save the network data(Y/N)?");
	  scanf("%s",chyn);
	  if(chyn[0]=='Y'||chyn[0]=='y')
	  {
		  saveparameter(layernum,n,k,w,b);
	  }	 
	}

   else
	 {
		 readparameter(&layernum,n,&k,w,b);
	 }

	 do
	 {
		input(n,y);
	   feedforward(layernum,n,k,y,w,b);
	 output(layernum,n,k,y);
	 printf("\nDo you want to output again(Y/N)?");
	 scanf("%s",chyn);
	 }while(chyn[0]=='Y'||chyn[0]=='y');
}




//信息前向传送
static void feedforward(int layernum,int n[],int k,double y[],double w[],double b[])
{
  int i,j,l;
  double u;
   
 for(l=1;l<layernum;l++)
 {
  for(j=0;j<n[l];j++)
  {
	  u=0.0;
	  for(i=0;i<n[l-1];i++)
	  {
		  u=u+w[(l*k+i)*k+j]*y[(l-1)*k+i];
		 
	  }
			u=u+b[l*k+j];
			y[l*k+j]=f(u);
  } 
  } 	
  
}


//误差反向传播（计算 ）
static void calcdelta(int layernum,int n[],int k,double d[],double y[],double w[],double delta[])
{
  int i,j,l,l1;
   for(j=0;j<n[layernum-1];j++)
  {
	  l1=layernum-1;
       
		delta[l1*k+j]=(d[j]-y[l1*k+j])*fd(y[l1*k+j]);
		  

  }
  for(l=layernum-2;l>0;l--)
  {
	  for(j=0;j<n[l];j++)
  {
		  delta[l*k+j]=0.0;
  for(i=0;i<n[l+1];i++)
  {
	  delta[l*k+j]+=delta[(l+1)*k+i]*w[((l+1)*k+j)*k+i];
  }

	delta[l*k+j]=fd(y[l*k+j])*delta[l*k+j];
    }
 }

}

//更新连接权值 和阈值 
static void update(int layernum,int n[],int k,double y[],double delta[],double miu,double w[],double b[])
{
 int i,j,l;
 for(l=1;l<layernum;l++)
 {
	 for(j=0;j<n[l];j++)
  {
		 for(i=0;i<n[l-1];i++)
		 {
			 w[(l*k+i)*k+j]+=miu*delta[l*k+j]*y[(l-1)*k+i];
		 }

		 b[l*k+j]+=miu*delta[l*k+j];
}
	}    

}

//计算S型函数的值
static double f(double x)

{
 double f1;
 f1=1.0/(1.0+exp(-x));
  
 return(f1);

}

//计算S型函数的导数值
static double fd(double x)

{
 double fd1;
 fd1=x*(1-x);
 return(fd1);
}

//初始化权值 和阈值 

double uniform(double a,double c,long int *seed)
{double t;
*seed=2045*(*seed)+1;
*seed=*seed-(*seed/1048576)*1048576;
t=(*seed)/1048576.0;
t=a+(c-a)*t;
return (t);
}


static void init(int layernum,int n[],int k,double w[],double b[])
{
 int i,j,l;
long int seed;
double uniform(double,double,long int *);

seed=13579l;

 for(l=1;l<layernum;l++)
 {
	 for(j=0;j<n[l];j++)
	 {
		 for(i=0;i<n[l-1];i++)
		 {
			 w[(l*k+i)*k+j]=uniform(0.0,1.0,&seed);
		 	 
		 }

		
          b[l*k+j]=uniform(0.0,1.0,&seed);
		 
	 }
  }

  }
  
//输入网络的输入模式
static void input(int n[],double y[])
{
 int j;
 printf("\n Input of feed");
 for(j=0;j<n[0];j++)
 {
  printf("\n\nInput pattern Y(0,%d)=",j);
  scanf("%lf",&y[j]);
 }
}

//输出（显示）网络的结果
static void output(int layernum,int n[],int k,double y[])
{
 int j;
 printf("\nOutput of feed\n");
 for(j=0;j<n[layernum-1];j++)
 {
	 printf("\nY(%d,%d)=%lf",layernum-1,j,y[(layernum-1)*k+j]);
 }
}

//存储网络的各种参数
static void saveparameter(int layernum,int n[],int k,double w[],double b[])
{
 int i,j,l;
 char fname1[14];
 FILE *fp;
 puts("\nInput the name of network data file:");
 scanf("%s",fname1);
 if((fp=fopen(fname1,"a"))==NULL)
 {
  puts("\ncannot open file");
  return;
 }

 fprintf(fp,"%d\n",layernum);
 for(l=0;l<layernum;l++)
 {
	 for(j=0;j<n[l];j++)
	 {
		 fprintf(fp,"%lf\n",b[l*k+j]);
		 for(i=0;i<n[l-1];i++)
		 {
			 fprintf(fp,"%lf\n",w[(l*k+i)*k+j]);
		 }
	 }
 }
 fclose(fp);
}

//读取网络的各种参数
static void readparameter(int *layernum,int n[],int *k,double w[],double b[])
{
 int i,j,l;
 char fname2[14];
 FILE *fp;
 puts("\nInput the name of trained network data file");
 scanf("%s",fname2);
 if((fp=fopen(fname2,"r"))==NULL)
 {
  puts("\ncannot open file");
  return;
 }
 fscanf(fp,"%d",layernum);
 for(l=0;l<(*layernum);l++)
 {
	 fscanf(fp,"%d",&n[l]);}
	 *k=n[0];
	 for(l=1;l<(*layernum);l++)
	 {
		 if(*k<n[l]) *k=n[l];}
		for(l=1;l<(*layernum);l++)
		{
			for(j=0;j<n[l];j++)
			{
				fscanf(fp,"%lf",&b[l*(*k)+j]);
				for(i=0;i<n[l-1];i++)
				{
					fscanf(fp,"%lf",&w[(l*(*k)+i)*(*k)+j]);
				}
	 }
	 }
fclose(fp);
}