new method for order parameter.m

来自「协同神经网络的程序」· M 代码 · 共 77 行

%A is the order parameter
maxA = -1000;
minA = 1000;


for k=1:NumOfImage
   %伪逆法
   %A(1,k)=VV(k,:)*Q;
   
   %距离法
   %A(1,k)=1-norm((v(k,:)-Q'))/2;
   
   %相关系数法
   %A(1,k)=sum(sum((v(k,:).*Q')))/sqrt(sum(sum(v(k,:).*v(k,:)))+sum(sum(Q.*Q)));
   
   %绝对值距离
   %A(1,k)=1-sum(sum(abs(v(k,:)-Q')))/(maxa);
   
   %信噪比
   e = norm((v(k,:)-Q'))^2;
   s = norm(v(k,:))^2; 
   %snr = log(s/(e));
   snr = s/e;
   %A(1,k)=snr;
   
   %直接法
   A(1,k)=v(k,:)*Q;
   
   if(A(k)>maxA) maxA = A(k);end
   if(A(k)<minA) minA = A(k);end
end
%A
%pause


%序参量演化方程
%baojie 2001-05-21

%the number of order parameter
NumberOfOP = NumOfImage;
%the number of step
NumberOfStep = 400;

%prepare attention parameter
for m=1:NumberOfOP
%    lmd(m)=1;
     lmd(m)=1-abs(vmean(m)-Qmean)/max(Qmean,255-Qmean);
end
%lmd(1)=1.2;

maxL = -1000;
minL = 1000;
for k=1:NumberOfOP
   if(lmd(k)>maxL) maxL = lmd(k);end
   if(lmd(k)<minL) minL = lmd(k);end
end
   
%parameter
B=1;C=1;

for n=1:NumberOfStep
%    n
    %global field 
    D(n)=0;
    for m=1:NumberOfOP
      D(n)=D(n)+(B+C)*A(n,m)*A(n,m);
    end
    
    %evloution function
    speed = 0.1/D(n);
    %speed = 0.3;
    
    for k=1:NumberOfOP
      A(n+1,k)=speed * A(n,k)*(lmd(k)-D(n)+B*A(n,k)*A(n,k))+A(n,k);
    end
    
    %