Tuner Upper Removal Demonstration: Difference between revisions
Jump to navigation
Jump to search
No edit summary |
No edit summary |
||
Line 1: | Line 1: | ||
<nowiki> |
|||
% Demonstration of LMS algorithm for noise cancellation. Tuner upper problem. |
|||
% Rich Kozick, Spring 1997 |
% Rich Kozick, Spring 1997 |
||
% Rob Frohne's modifications for Macintosh 2000 |
% Rob Frohne's modifications for Macintosh 2000 |
||
Line 46: | Line 47: | ||
skip =1000; |
skip =1000; |
||
soundsc(e(skip:length(e)),Fs); |
soundsc(e(skip:length(e)),Fs); |
||
</nowiki> |
Latest revision as of 13:43, 6 December 2015
% Demonstration of LMS algorithm for noise cancellation. Tuner upper problem. % Rich Kozick, Spring 1997 % Rob Frohne's modifications for Macintosh 2000 % and Linux 2006 or so. clear all Fs=8000; % 8 Khz sampling for Linux. T0 = 2; % 2 seconds system("espeak 'After hitting enter in the command window, speak the signal.'"); st = record(T0,Fs); %st=wavread('Hello.wav'); st=st(:,1); system("espeak 'Here is the signal.'") soundsc(st); Ls = length(st); T0=length(st)/Fs; % Make the tuner upper noise or even several at the same time. t=0:1/Fs:T0-1/Fs; n = 10*(sin(2*pi*100*pi*t) + cos(2*pi*600*t) + 1.5*sin(2*pi*850*t)); % Add him or them to the desired signal. x = st' + n; system("espeak 'Here is the noisy signal.'") soundsc(x,Fs); N = 64; % Length of adaptive filter % LMS algorithm for adaptive noise cancellation h = ones(N,1); mu = 0.1; for k=N:Ls xk = x(k:-1:(k-N+1)); y(k) = h'*xk'; e(k) = y(k); h = h - 2*mu*e(k)*xk'/(xk*xk'); end % The signal estimate is in the vector e system("espeak 'Here is a scaled version of the tail of the cleaned signal.'"); skip =1000; soundsc(e(skip:length(e)),Fs);