wavenetwork.m

用小波构造神经网络

clear all
load data
M1=20;
epo=15;
A=4;
B=18;
B2=B/2+1
N=500;
M=(A+1)*(B+1);
for  a0=1:A+1;
for  b0=1:B+1;
i=(B+1)*(a0-1)+b0;
b_init(i)=((b0-B2)/10)/(2^(-A)); a_init(i)=1/(2^(-A));
c_init(i)=(20-A)/2;
end 
end 
w0=ones(1,M);
          for i=1:N             
              for j=1:M           
                  t=x(i);
                  t= a_init(j)*t-b_init(j);
                 %P0(i,j)= (cos(1.75*t)*exp(-t*t/2))/2^c_init(j); 
                 P0(i,j)= ((1-t*t)*exp(-t*t/2))/2^c_init(j); 
             end
          end
%calculation of output of network
           for i=1:N
                 u=0;
                 for j=1:M
                     u=u+w0(j)*P0(i,j);%w0?aè¨?μ
                 end
                 y0(i)= u;% y(p)= u=??W(j)*phi(p,j)= ??W(j)* |μj(t)
           end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% 
for k=1:M
    W(:,k)=P0(:,k);
end
for k=2:M
    u=0;
   
     for      i=1:k-1    
              aik(i)=(P0(:,k)'*W(:,i))/(W(:,i)'*W(:,i));
              u=u+aik(i) *W(:,i);
              
     end
     W(:,k)=P0(:,k)-u;
end

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

for   i=1:M                         
     g(i)= (W(:,i)'*d')/( W(:,i)'* W(:,i)); 
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
u=0;
for    i=1:M
       u=u+g(i)*(W(:,i)'*W(:,i));
end

DD=u;

for    i=1:M
       Erro(i)=(g(i)^2)*(W(:,i)'*W(:,i))/DD;
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
k=1;

while(k<=M1)
    u=1;
    for  i=2:M
         if   abs(Erro(u))<abs(Erro(i));
              u=i
         else u=u
         end
    end
    I(k)=u;
    Erro(u)=0
k=k+1;  
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% 
for k=1:M1
    u=I(k);
    a(k)=a_init(u);
    b(k)=b_init(u);
    c(k)=c_init(u);
    w1(k)=w0(u);
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
epoch=1;

error=0.1;
err=0.0001;
lin=0.5;

while (error>=err & epoch<=epo)
          for i=1:N             
              for j=1:M1        
                  t=x(i);
                  t= a(j)*t-b(j);
                 %P1(i,j)= (cos(1.75*t)*exp(-t*t/2))/2^c(j); 
                 P1(i,j)= ((1-t*t)*exp(-t*t/2))/2^c(j); 
             end
          end
%calculation of output of network
           for i=1:N
                 u=0;
                 for j=1:M1
                     u=u+w1(j)*P1(i,j);
                 end
                 y1(i)= u;
           end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
   u=0;
     for i=1:N
            u=u+(d(i)-y1(i))^2;
     end
    u=u/2;%u=1/2??(d-p)^2
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
if   u>error
lin=lin*0.8;
else
lin=lin*1.2;
end
error=u; %error=u=1/2??(d-p)^2
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
         for j=1:M1   
             u=0;
             for i=1:N
                 u=u+(d(i)-y1(i))*P1(i,j);
             end
             EW(j)=-u;
          end
   if    epoch==1
       SW=-EW;
       w1_=w1;
       
   else
   SW=-EW+((EW*EW')*SW_)/(EW_*EW_');
   end
   EW_=EW;
   SW_=SW;
    w1=w1_+SW*lin;
    w1_=w1;
  
    %number of epoch increase by 1
epoch=epoch+1;
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
subplot(2,1,1);plot(x,d);
subplot(2,1,2);plot(x,y1);