getscatter.m

来自「使用Fisher线性鉴别分析（FLDA）方法在ORL人脸数据库上进行人脸识别试验」· M 代码 · 共 40 行

function [Sb,Sw,St]=GetScatter(Sample)
%求输入矩阵Sample的散度矩阵
%输入：Sample为待求样本矩阵
%输出：Sb为Sample的类间散布矩阵，Sw为Sample的类内散布矩阵，St为Sample的总体散布矩阵

[dim,N,C]=size(Sample);       %N--每类样本的样本容量，C--类别数
Mean=zeros(dim,C);
for t=1:C
   sum=zeros(dim,1);
   for k=1:N
      sum=sum+Sample(:,k,t);
   end
   Mean(:,t)=(1/N)*sum;
end
%find Sw:
Sw=zeros(dim,dim);
Transcendental_prob=1/C; 
Sc=zeros(dim,dim,C);
for t=1:C
    for k=1:N
      V=Sample(:,k,t)-Mean(:,t);
      Sw=Sw+V*V';
    end
end
Sw=Sw.*(Transcendental_prob/N);  
%find Sb:
S=zeros(dim,dim);
m=zeros(dim,1);
for t=1:C
   m=m+Mean(:,t);
end
m=Transcendental_prob.*m;
for t=1:C
   V=Mean(:,t)-m;
   S=S+V*V';
end
Sb=Transcendental_prob.*S;
%find St
St=Sb+Sw;