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demo1.m
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demo1.m
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% ------------------------------------------------------------------------
% Copyright (C)
% LiXirong - Wuhan University, China
%
% LiXirong <[email protected]> or <[email protected]>
% 2018.12.21
% ------------------------------------------------------------------------
%
% demo1.m - adaptive filter demo（自适应滤波算法应用demo）
% Including LMS、NLMS、RLS algorithm
% Including：
% 1、echo cancellation 音频回声消除
% 2、audio + white noise 音频白噪声消除
% 3、audio + single frequency noise 音频+单频噪声消除
% 4、single frequency signal + white noise 单频信号+白噪声消除
% 5、multi-frequency signal + single frequency signal noise 多频信号+单频声消除
% Parameters：
% x ： input signal 输入信号
% d ： reference signal 参考信号
% y ： output signal 输出信号
% e ： error signal 误差信号
% mu ： LMS stepsize LMS算法步长
% mu2 ： NLMS stepsize NLMS算法步长
% a ： NLMS bias NLMS算法偏置参数
% lamda ： RLS weight RLS算法权重
%
% ------------------------------------------------------------------------
close all;clear;clc;
%% 1、echo cancellation (音频回声)
% [d, fs] = audioread('handel.wav');
% x = audioread('handel_echo.wav');
% mu = 0.05;
% mu2 = 0.05;
% a = 0.1;
% lamda = 0.99;
% M = 40;
%% 2、audio + white noise (音频+白噪声)
% [d,fs] = audioread('handel.wav');
% n = length(d);
% noise = wgn(1, n, -20)';
% x = d + noise;
% mu = 0.001;
% mu2 = 0.1;
% a = 0.01;
% lamda = 0.99;
% M = 80;
%% 3、audio + single frequency noise (音频+单频噪声)
% [d, fs] = audioread('handel.wav');
% n = length(d);
% T = n/fs;
% t = 0:1/fs:T-1/fs;
% noise = cos(2*pi*t*370)';
% x = d + noise;
%
% mu = 0.005;
% mu2 = 0.05;
% a = 0.1;
% lamda = 0.9999;
% M = 40;
%% 4、single frequency signal + white noise (单频+白噪声)
fs = 8000;
t = 0:1/fs:5;
noise = wgn(1, length(t),-20)';
d = cos(2*pi*t*261.625)';
x = noise + cos(2*pi*t*261.625)';
mu = 0.0001;
mu2 = 0.001;
a = 0.1;
lamda = 0.999;
M = 40;
%% 5、multi-frequency signal + single frequency signal noise (多频+单频噪声)
% fs = 16000;
% t = 0:1/fs:4;
% d = cos(2*pi*t*200)';
% x = cos(2*pi*t*100)' + d;
% mu = 0.01;
% mu2 = 0.1;
% a = 0.1;
% lamda = 0.9999;
% M = 50;
%% LMS\NLMS\RLS performance (LMS\NLMS\RLS性能比较)
% run algorithm (运行算法并计算时间)
tic
[e1, y1, w1] = myLMS(d, x, mu, M);
toc
tic
[e2, y2, w2] = myNLMS(d, x,mu2, M, a);
toc
tic
[e3, y3, w3] = myRLS(d, x,lamda,M);
toc
% 画出输入信号、参考信号、滤波输出、误差
figure()
subplot(4,2,1)
plot([1:length(x)]/fs,x);
xlabel('time');
title('x(n)');
subplot(4,2,2)
plot([1:length(d)]/fs,d);
xlabel('time');
title('d(n)');
subplot(4,2,3)
plot([1:length(y1)]/fs,y1);
xlabel('time');
title('LMS y(n)');
subplot(4,2,5)
plot([1:length(y2)]/fs,y2);
xlabel('time');
title('NLMS y(n)');
subplot(4,2,7)
plot([1:length(y3)]/fs,y3);
xlabel('time');
title('RLS y(n)');
subplot(4,2,4)
plot([1:length(e1)]/fs,e1);
xlabel('time');
title('LMS e(n)');
subplot(4,2,6)
plot([1:length(e2)]/fs,e2);
xlabel('time');
title('NLMS e(n)');
subplot(4,2,8)
plot([1:length(e3)]/fs,e3);
xlabel('time');
title('RLS e(n)');