hk.asv

用于模式识别分类

function HK(Sample1,Sample2);
n1=size(Sample1);
for i=1:n1(1)
   ExtendSample1(i,:)=[Sample1(i,:) 1];  %样本1分量增广化，训练样本增加分量1
end;

n2=size(Sample2);
for i=1:n2(1)
   ExtendSample2(i,:)=[Sample2(i,:) 1];  %样本2分量增广化，训练样本增加分量1
end;

ExtendSample2=-1.*ExtendSample2;  %训练样本2乘以-1
Sample=[ExtendSample1;ExtendSample2];
n=size(Sample);
%求伪逆
FInvSample=inv(Sample'*Sample)*Sample';
e=ones(1,n(1))';
count=0;
%while e~=zeros(1,n(1))'||max(e)<0||count==100,   %终止循环条件
while min(e)>0||count~=100,   %终止循环条件,e(k)等于零种植循环，e(k)大于零继续下步，e(k)各份量均为
 b=ones(1,n(1))';%余量矢量赋初值
 p=1;%赋P=1
 w=FInvSample*b;
 e=Sample*w-b;

 if min(e)>0   
   w=w+p*FInvSample*abs(e);
   b=b+p*(abs(e)+e);
 end;
 count=count+1;  %%%将循环次数控制在100以内
end;
Sample
w
e