bss_main.m

这是盲信号的代码 都已经通过编译了 做这方面的同仁可以参考一下 我觉得蛮惯用的

%主函数:
A=[1.5,1;1,1.4];                                          %给定混合矩阵A
A1=inv(A);                                                %A1为A的逆
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s2=[-0.0015385	0	-0.00076923	-0.012692	0.0038462	-0.0076923	-0.011538	0.0046154	-0.017308	0.0046154	-0.00076923	-0.0092308	0.011538	-0.0092308	0.00076923	0.0084615	-0.0046154	0.0038462	0.018846	-0.01	0.023462	0.0015385	-0.0038462	0.034231	-0.025	0.025	-0.0084615	-0.010769	0.038077	-0.026538	0.023462	0.0061538	-0.038077	0.056538	-0.038077	0.012692	0.028077	-0.068846	0.095	-0.078077	0.035769	0.026538	-0.088846	0.11346	-0.084231	0.023462	0.038077	-0.10115	0.11962	-0.081154	0.018846	0.068846	-0.13808	0.16269	-0.11962	0.038077	0.071923	-0.16885	0.215	-0.18115	0.10115	0.023462	-0.16269	0.22731	-0.23962	0.175	-0.044231	-0.10115	0.215	-0.27654	0.25192	-0.12577	-0.020385	0.16269	-0.25192	0.27654	-0.215	0.10731	0.044231	-0.18115	0.26423	-0.26423	0.19038	-0.062692	-0.075	0.19038	-0.23962	0.23962	-0.15654	0.053462	0.084231	-0.18115	0.22731	-0.22731	0.15038	-0.021923	-0.095	0.20269	-0.25192	0.215	-0.12577	0.011538	0.10115	-0.20269	0.22731	-0.19038	0.13808	0	-0.095	0.175	-0.20269	0.175	-0.084231	0.014231	0.062692	-0.13808	0.16885	-0.16269	0.12577	-0.056538	-0.014231	0.081154	-0.10731	0.12577	-0.12577	0.10115	-0.047308	0.029615	0.0030769	-0.084231	0.13808	-0.15038	0.14423	-0.071923	-0.0076923	0.056538	-0.047308	0.088846	-0.13192	0.13808	-0.12577	0.053462	0.078077	-0.13808	0.11962	-0.081154	0.050385	-0.065769	0.084231	-0.065769	-0.035769	0.19038	-0.23962	0.175	-0.018846	-0.11962	0.16269	-0.084231	-0.021923	0.034231	0.010769	-0.053462	0.044231	0.050385	-0.14423	0.13192	0.017308	-0.11962	0.16885	-0.088846	-0.050385	0.13192	-0.038077	-0.078077	0.10731	-0.056538	-0.088846	0.19038	-0.11346	-0.053462	0.15038	-0.12577	0	0.14423	-0.13808	-0.012692	0.14423	-0.11962	0.012692	0.11962	-0.15654	0.015769	0.13808	-0.11962	-0.012692	0.14423	-0.16269	0.020385	0.215	-0.25192	0.059615	0.16885	-0.25192	0.15038	0.088846	-0.25192	0.14423	0.12577	-0.23962	0.15654	0.071923	-0.26423	0.22731	0.062692	-0.28885	0.215	0.023462	-0.26423	0.30115	-0.044231	-0.23962	0.30115	-0.075	-0.215	0.31346	-0.12577	-0.18115	0.33808	-0.19038	-0.13192	0.32577	-0.23962	-0.071923	0.33808	-0.30115	-0.028077	0.33808	-0.32577	0.044231	0.32577	-0.39346	0.10115	0.32577	-0.44269	0.19038	0.22731	-0.46731	0.27654	0.15654	-0.41808	0.28885	0.11346	-0.39346	0.30115	0.075	-0.39346	0.33808	0.044231	-0.36269	0.35038	0.014231	-0.35038	0.36269	-0.0038462	-0.39346	0.41808	-0.053462	-0.39346	0.49192	-0.15654	-0.32577	0.49192	-0.20269	-0.26423	0.44269	-0.20269	-0.23962	0.44269	-0.20269	-0.22731	0.44269	-0.215	-0.22731	0.44269	-0.20269	-0.22731	0.44269	-0.22731	-0.19038	0.44269	-0.22731	-0.16269	0.375	-0.22731	-0.13192	0.36269	-0.20269	-0.14423	0.31346	-0.15654	-0.14423	0.32577	-0.16269	-0.19038	0.35038	-0.15654	-0.18115	0.33808	-0.16269	-0.19038	0.35038	-0.15038	-0.215	0.35038	-0.13192	-0.22731	0.375	-0.12577	-0.23962	0.33808	-0.075	-0.25192	0.30115	-0.021923	-0.31346	0.30115	0.014231	-0.30115	0.27654	0.021923	-0.27654	0.215	0.088846	-0.28885	0.14423	0.15654	-0.30115	0.13808	0.20269	-0.33808	0.11962	0.215	-0.32577	0.10731	0.22731	-0.32577	0.078077	0.22731	-0.28885	0.026538	0.23962	-0.23962	-0.0084615	0.25192	-0.23962	-0.050385	0.27654	-0.22731	-0.044231	0.26423	-0.23962	-0.078077	0.31346	-0.19038	-0.13192	0.33808	-0.20269	-0.15654	0.39346	-0.22731	-0.175	0.39346	-0.22731	-0.18115	0.36269	-0.18115	-0.215	0.39346	-0.15038	-0.27654	0.39346	-0.11962	-0.27654	0.39346	-0.10115	-0.31346	0.375	-0.011538	-0.36269	0.33808	0.044231	-0.39346	0.31346	0.084231	-0.41808	0.25192	0.13808	-0.36269	0.19038	0.175	-0.33808	0.11962	0.215	-0.33808	0.071923	0.26423	-0.32577	0.029615	0.31346	-0.30115	-0.035769	0.33808	-0.31346	-0.056538	0.36269	-0.28885	-0.088846	0.31346	-0.22731	-0.084231	0.31346	-0.215	-0.12577	0.30115	-0.16269	-0.11962	0.27654	-0.12577	-0.15654	0.28885	-0.12577	-0.19038	0.27654	-0.095	-0.215	0.30115	-0.053462	-0.28885	0.33808	-0.038077	-0.31346	0.32577	-0.011538	-0.31346	0.27654	0.11962	-0.35038	0.175	0.19038	-0.32577	0.071923	0.26423	-0.27654	-0.056538	0.32577	-0.22731	-0.175	0.35038	-0.14423	-0.25192	0.36269	-0.059615	-0.32577	0.31346	0.059615	-0.35038	0.215	0.14423	-0.35038	0.15038	0.22731	-0.32577	0.041154	0.25192	-0.26423	-0.053462	0.33808	-0.25192	-0.11346	0.375	-0.22731	-0.13808	0.35038	-0.16269	-0.215	0.33808	-0.068846	-0.28885	0.31346	0.056538	-0.39346	0.27654	0.16885	-0.44269	0.23962	0.25192	-0.46731	0.15654	0.32577	-0.39346	-0.041154	0.375	-0.26423	-0.16269	0.41808	-0.175	-0.30115	0.39346	0.021923	-0.39346	0.26423	0.16269	-0.44269	0.22731	0.30115	-0.46731	0.032692	0.39346	-0.32577	-0.10115	0.44269	-0.26423	-0.26423	0.46731	-0.088846	-0.375	0.35038	0.075	-0.41808	0.23962	0.26423	-0.44269	0.050385	0.41808	-0.36269	-0.11962	0.44269	-0.22731	-0.27654	0.44269	-0.041154	-0.44269	0.33808	0.20269	-0.46731	0.16269	0.375	-0.46731	-0.034231	0.51654	-0.32577	-0.27654	0.54115	-0.11962	-0.46731	0.49192	0.088846	-0.59038	0.36269	0.31346	-0.56577	0.088846	0.49192	-0.46731	-0.16269	0.615	-0.28885	-0.41808	0.615	-0.012692	-0.59038	0.44269	0.27654	-0.66423	0.22731	0.51654	-0.615	-0.065769	0.68885	-0.41808	-0.375	0.68885	-0.12577	-0.615	0.56577	0.22731	-0.73808	0.26423	0.56577	-0.66423	-0.075	0.79962	-0.49192	-0.41808	0.79962	-0.13192	-0.68885	0.59038	0.25192	-0.79962	0.28885	0.59038	-0.68885	-0.10731	0.76269	-0.41808	-0.44269	0.73808	-0.056538	-0.71346	0.54115	0.35038	-0.79962	0.19038	0.71346	-0.71346	-0.19038	0.89808	-0.41808	-0.56577	0.79962	0.020385	-0.84885	0.56577	0.46731	-0.84885	0.15038	0.76269	-0.66423	-0.30115	0.89808	-0.31346	-0.66423	0.76269	0.12577	-0.84885	0.44269	0.56577	-0.84885	0.012692	0.79962	-0.56577	-0.41808	0.84885	-0.14423	-0.73808	0.66423	0.32577	-0.89808	0.27654	0.71346	-0.76269	-0.175	0.89808	-0.44269	-0.615	0.84885	0.018846	-0.79962	0.51654	0.46731	-0.79962	0.059615	0.73808	-0.51654	-0.41808	0.79962	-0.10731	-0.73808	0.615	0.35038	-0.84885	0.23962	0.73808	-0.73808	-0.22731	0.84885	-0.35038	-0.59038	0.73808	0.11346	-0.79962	0.39346	0.56577	-0.71346	-0.065769	0.73808	-0.41808	-0.44269	0.73808	-0.017308	-0.71346	0.46731	0.41808	-0.71346	0.062692	0.63962	-0.46731	-0.30115	0.66423	-0.075	-0.615	0.44269	0.33808	-0.615	0.068846	0.59038	-0.41808	-0.33808	0.68885	-0.095	-0.59038	0.46731	0.28885	-0.615	0.11346	0.51654	-0.44269	-0.22731	0.59038	-0.10115	-0.51654	0.41808	0.26423	-0.56577	0.10731	0.49192	-0.41808	-0.26423	0.63962	-0.10731	-0.54115	0.39346	0.25192	-0.59038	0.10731	0.59038	-0.49192	-0.26423	0.63962	-0.13192	-0.49192	0.44269	0.23962	-0.59038	0.10115	0.56577	-0.46731	-0.28885	0.63962	-0.13808	-0.51654	0.44269	0.23962	-0.59038	0.10115	0.54115	-0.41808	-0.27654	0.56577	-0.047308	-0.51654	0.375	0.30115	-0.56577	0.020385	0.615	-0.39346	-0.31346	0.56577	-0.065769	-0.49192	0.36269	0.31346	-0.54115	-0.020385	0.54115	-0.27654	-0.36269	0.49192	0.047308	-0.51654	0.28885	0.41808	-0.51654	-0.13192	0.56577	-0.23962	-0.375	0.46731	0.071923	-0.49192	0.20269	0.36269	-0.39346	-0.15038	0.44269	-0.11962	-0.35038	0.33808	0.14423	-0.41808	0.088846	0.36269	-0.30115	-0.19038	0.41808	-0.065769	-0.375	0.28885	0.175	-0.39346	0.050385	0.33808	-0.215	-0.22731	0.35038	0.028077	-0.36269	0.20269	0.26423	-0.35038	-0.068846	0.41808	-0.15654	-0.28885	0.31346	0.068846	-0.33808	0.12577	0.27654	-0.23962	-0.14423	0.31346	-0.021923	-0.27654	0.18115	0.175	-0.30115	-0.031154	0.32577	-0.14423	-0.25192	0.30115	0.059615	-0.33808	0.12577	0.22731	-0.25192	-0.10115	0.28885	-0.053462	-0.26423	0.20269	0.15654	-0.26423	0.0053846	0.26423	-0.15038	-0.20269	0.23962	0.088846	-0.28885	0.081154	0.23962	-0.22731	-0.11962	0.27654	-0.028077	-0.26423	0.175	0.15654	-0.22731	-0.017308	0.25192	-0.11962	-0.19038	0.22731	0.071923	-0.23962	0.053462	0.215	-0.16885	-0.10115	0.23962	-0.044231	-0.19038	0.13808	0.13808	-0.175	-0.050385	0.16885	-0.050385	-0.13808	0.12577	0.088846	-0.19038	-0.010769	0.18115	-0.081154	-0.11346	0.11962	0.021923	-0.11962	0.035769	0.10115	-0.062692	-0.088846	0.081154	0.047308	-0.084231	-0.010769	0.095	-0.026538	-0.088846	0.068846	0.044231	-0.075	-0.0092308	0.056538	0.0076923	-0.062692	-0.010769	0.088846	-0.0092308	-0.075	0.062692	0.047308	-0.088846	-0.0076923	0.10115	-0.020385	-0.095	0.041154	0.062692	-0.050385	-0.034231	0.047308	0.012692	-0.065769	-0.0061538	0.088846	-0.01	-0.095	0.062692	0.053462	-0.071923	-0.0069231	0.047308	-0.0038462	-0.031154	-0.0030769	0.028077	0.011538	-0.035769	0.0076923	0.068846	-0.015769	-0.062692	0.056538	0.028077	-0.047308	0.0084615	0.015769	-0.017308	-0.011538	0.0084615	0.017308	0.014231	-0.044231	-0.023462	0.053462	-0.0030769	-0.023462	0.029615	-0.01	-0.010769	0.017308	-0.0084615	0.010769	0.0069231	-0.059615	0.0030769	0.065769	-0.029615	-0.035769	0.056538	-0.014231	-0.031154	0.035769	-0.01	0.0061538	0.0030769	-0.038077	0.026538	0.014231	-0.041154	0.023462	0.041154	-0.038077];
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%s1和s2为两路语音源信号
S=[s1;s2];                                                %S为源信号矩阵。
X=A*S;                                                    %X为混合信号矩阵
x1=X(1,:);                                                %x1和x2为两个混合信号
x2=X(2,:);
W=BSS(X);                                                 %由函数W=BSS(X)得到分离阵W
G=W(:,:,801)*A;
l=size(W);
Y=W(:,:,l(3))*X;                                          %得到源信号S的估计Y
y1=Y(1,:);                                                %估计信号y1和y2分别是对s1和s2的估计
y2=Y(2,:);