b.m

递归最小二乘滤波器算法

fid1=fopen('G:\研究生课程\随机信号处理\LMS\f1.dat','r');
signal=fread(fid1,64000,'short');
fclose(fid1);

fid2=fopen('G:\研究生课程\随机信号处理\LMS\f1-white.dat','r');
noisy=fread(fid2,64000,'short');
fclose(fid2);

fid3=fopen('G:\研究生课程\随机信号处理\LMS\f1out.dat','r');
out=fread(fid3,64000,'short');
fclose(fid3);

fid4=fopen('G:\研究生课程\随机信号处理\LMS\mse.dat','r');
mse=fread(fid4,64000,'double');
fclose(fid4);

fid5=fopen('G:\研究生课程\随机信号处理\LMS\whiten.dat','r');
noise=fread(fid5,64000,'short');
fclose(fid5);

n = noise.*noise;

figure(1);
subplot(3,1,1); plot(signal); title('Clean Signal Waveform'); xlabel('Time'); ylabel('Amplitude');
subplot(3,1,2); plot(noise); title('Noise Waveform'); xlabel('Time'); ylabel('Amplitude');
subplot(3,1,3); plot(noisy); title('Noisy Signal Waveform'); xlabel('Time'); ylabel('Amplitude');

figure(2);
subplot(3,1,1); plot(signal); title('Clean Speech Waveform'); xlabel('Time'); ylabel('Amplitude');
subplot(3,1,2); plot(out); title('Filtered Speech Waveform'); xlabel('Time'); ylabel('Amplitude');
subplot(3,1,3); plot(n,'r'); title('Squared error'); hold; plot(mse);