103244862adaptive_LMS.rar_LMS算法程序_lms C_lms程序_lms自适应算法c_自适应算法c

% ==================================================== % LMS method for noise cancellation %----------------use audio signal "good morning"-------------------------------------- % ==================================================== clear; clc; disp(' ========================='); disp(' LMS '); disp(' ========================='); % --------- Initialization ---------- hord=20; % ---------- signal and noise generation ----------- s=wavread('sound'); len=length(s); n=1:len; v=(sin(0.6*n)+2*sin(2*pi*n)+sin(0.5*n))'; %噪声 x=(sin(0.6*n)+sin(2*pi*n+0.8)+sin(0.5*n+2*pi))'; %参考输入 d=s+10*v; wavwrite(x,15000,16,'daizao'); ws=zeros(hord+1,len-hord); errs=zeros(len,1); mus=0.008; % --------- LMS noise cancellation --------- for i=hord+1:len-hord j=i-hord:1:i; x1=x(j); ys(i)=ws(:,i)'*x1; errs(i)=d(i)-ys(i); q(i)=errs(i)-s(i); n1=hord+1;n2=len-hord; Eq(i)=sum(abs(q(i)).^2); Pq(i)=Eq(i)/(n2-n1); ws(:,i+1)=ws(:,i)+mus*x1*errs(i); end % WAVWRITE(Y,FS,WAVEFILE) wavwrite(errs,15000,'shuchu'); figure(1) plot(s),title('original'); figure(2) plot(d),title('noisy signal'); figure(3) plot(errs),title('output'); % ERROR EFFICIENCY figure(4) plot(Pq),title('error efficency'); figure(5) plot(ws(10,:)),title('converge line')