%基于負(fù)熵最大的FASTICA
fs=1000;
N=1024;
t=（0:N-1）/fs;
f1=60;
f2=150;
f3=200;
I1=sin（2*pi*f1*t）;
I2=cos（2*pi*f2*t）;
I3=randn（size（t））;
%?I3=sin（2*pi*f3*t）;
subplot（431）plot（I1）title（‘輸入信號1‘）axis（[0100-44]）;
subplot（432）plot（I2）title（‘輸入信號2‘）axis（[0100-44]）;
subplot（433）plot（I3）title（‘輸入信號3‘）axis（[0100-44]）;

%?將其組成矩陣
S=[I1;I2;I3];??????????????????????????%?信號個數(shù)即為變量數(shù)
???????????????????????????????????????%?因此S_all是一個變量個數(shù)＊采樣個數(shù)的矩陣
Sweight=rand（size（S1））;???????????????%?取一隨機矩陣，作為信號混合的權(quán)矩陣
MixedS=Sweight*S;??????????????????????%?得到三個信號的混合信號矩陣

%?將混合矩陣重新排列并輸出
subplot（434）plot（MixedS（1:））title（‘混合信號1‘）axis（[0100-44]）;
subplot（435）plot（MixedS（2:））title（‘混合信號2‘）axis（[0100-44]）;
subplot（436）plot（MixedS（3:））title（‘混合信號3‘）axis（[0100-44]）;
MixedS_bak=MixedS;?????????????????????????%?將混合后的數(shù)據(jù)備份，以便在恢復(fù)時直接調(diào)用
%%%%%%%%%%%%%%%%%%%%%%%%%%??標(biāo)準(zhǔn)化??%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
MixedS_mean=zeros（31）;
for?i=1:3
????MixedS_mean（i）=mean（MixedS（i:））;
end????????????????????????????????????????%?計算MixedS的均值

for?i=1:3
????for?j=1:size（MixedS2）
????????MixedS（ij）=MixedS（ij）-MixedS_mean（i）;
????end
end

%%%%%%%%%%%%%%%%%%%%%%%%%%%??白化??%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

MixedS_cov=cov（MixedS‘）;????????????????????%?cov為求協(xié)方差的函數(shù)
[ED]=eig（MixedS_cov）;??????????????????????%?對信號矩陣的協(xié)方差函數(shù)進(jìn)行特征值分解
Q=inv（sqrt（D））*（E）‘;????????????????????????%?Q為白化矩陣
MixedS_white=Q*MixedS;??????????????????????%?MixedS_white為白化后的信號矩陣
IsI=cov（MixedS_white‘）;?????????????????????%?IsI應(yīng)為單位陣????????????

%%%%%%%%%%%%%%%%%%%%%%%%　FASTICA算法??%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
X=M