fast ICA的Matlab代码

clc;clear all;close all;
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（‘输入信号1‘）axis（[0100-44]）;
subplot（432）plot（I2）title（‘输入信号2‘）axis（[0100-44]）;
subplot（433）plot（I3）title（‘输入信号3‘）axis（[0100-44]）;

% 将其组成矩阵
S=[I1;I2;I3];                        
Sweight=rand（size（S1））;               
MixedS=Sweight*S;     % 将混合矩阵重新排列并输出
subplot（434）plot（MixedS（1:））title（‘混合信号1‘）axis（[0100-44]）;
subplot（435）plot（MixedS（2:））title（‘混合信号2‘）axis（[0100-44]）;
subplot（436）plot（MixedS（3:））title（‘混合信号3‘）axis（[0100-44]）;
MixedS_bak=MixedS;                  
%%%%%%%%%%%%%%%%%%%%%%%%%%  标准化  %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
MixedS_mean=zeros（31）;
for i=1:3
    MixedS_mean（i）=mean（MixedS（i:））;
end                                        % 计算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为求协方差的函数
[ED]=eig（MixedS_cov）;                      % 对信号矩阵的协方差函数进行特征值分解
Q=inv（sqrt（D））*（E）‘;                        % Q为白化矩阵
MixedS_white=Q*MixedS;                      % MixedS_white为白化后的信号矩阵
IsI=cov（MixedS_white‘）;                     % IsI应为单位阵            

%%%%%%%%%%%%%%%%%%%%%%%%　FASTICA算法  %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
X=MixedS_white;                            % 以下算法将对X进行操作
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