function?[F]=Sym_ICA1（varargin）


%此函數為基于對稱圖像矩陣的ICA人臉識別方法，其中訓練樣本為
%ORL庫中前20組的前五幅圖像。
%輸入（即測試樣本）為前20組的后五幅圖像，輸出為與輸入匹配的
%訓練樣本



%%%%%%%%%%%%%%%%%%%%%%%%%%??初始化??%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%?
?
clc;clear?all;close?all;?
?I1=imread（‘F:\project\ONE\king\try\ORL\s1\1.bmp‘）;
?[ab]=size（I1）;
?A=cell（ab）;
?B=cell（ab）;
?Ae=cell（ab）;
Ao=cell（ab）;
I=cell（a*b1）;
?N=20;
?M=1;
%%%%%%%%%%%%%%%%%%%%%%%%%%圖像讀入，求鏡像圖像?%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%?
for?i=1:N
????for?j=1:M
????A{（i-1）*M+j}=imread（strcat（‘F:\project\ONE\king\try\ORL\s‘num2str（i）‘\‘num2str（j）‘.bmp‘））;
????[heightwidth]=size（A{（i-1）*M+j}）;
????tform=maketform（‘affine‘[-1?0?0;0?1?0;width?0?1]）;
????B{（i-1）*M+j}=imtransform（A{（i-1）*M+j}tform‘nearest‘）;
?????Ae{（i-1）*M+j}=?（A{（i-1）*M+j}+B{（i-1）*M+j}）/2;
?????Ao{（i-1）*M+j}=?（A{（i-1）*M+j}-B{（i-1）*M+j}）/2;
????end;
?end;
?for??num=1:N*M
?????I{num}=reshape（A{num}[a*b?1]）;
??????X（:num）?=I{num};
?end

?
?%%%%%%%%%%%%%%%%%%%分別對奇對稱圖像矩陣和偶對稱圖像矩陣求均值%%%%%%%%%%%%%%%%%%%%%%%%%%%%?
?Xe=?0;
??Xo=?0;
?for?i=1:N*M
????Xe=?Xe+Ae{i};
????Xo=?Xo+Ao{i};
?end?
Xe=Xe/N;
Xo=Xo/N;

?%%%%%%%%%%%%%%%%%%%對稱樣本矩陣的協方差矩陣%%%%%%%%%%%%%%%%%%%%%%%%%%%%?
?Ge=?0;
?Go=?0;
?for?i=1:N*M
???Ge=Ge+double（（Ae{i}-Xe）‘）*double（Ae{i}-Xe）;
???Go=Go+double（（Ao{i}-Xo）‘）*double（Ao{i}-Xo）;
?end?
Ge=Ge/（N*M）;
Go=Go/（N*M）;

%%%%%%%%%%%%%%%%%%%ICA中的數據白化預處理%%%%%%%%%%%%%%%%%%%%%%%%%%%?
[EeDe]=eig（Ge）;
Vee=De^（-1/2）*Ee;
[EoDo]=eig（Go）;
Voo=Do^（-1/2）*Eo;
KK=zeros（bb*（a-1））;
Ve=[Vee?KK];
Vo=[Voo?KK];
for?i=1:N*M
????Ye=double（Ve）*double（X）;
????Yo=double（Vo）*double（X）;
end

%%%%%%%%%%%%%%%%%%%采用快速固定點迭代法算法計算解混矩陣分別計算Wde?和Wdo%%%%%%%%%%%%%%%%%%%%%%%%%%%?

[xy]=size（Ye）;
maxcount=10000;
critical=0.00001;
?Wde=rand（x）;
??for?n=1:x
???????w=Wde（:n）;
???????count=0;
???????Wde（:n）=Wde（:n）/norm（Wde（:n））;????????lastwp=zeros（x1）;

???????while?abs（w-lastwp）&abs（w+lastwp）>critical
?????????????????count=count+1;
?????????????????l