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From: Arrate Alonso on 7 Nov 2007 06:35
Dear Mr Teyhan,

I'm a student and I'm currently working on something very
similar to your code of the post. How did you solve the
problem?

Thanks

"kevin teyhan" <kevinteyhan(a)hotmail.com> wrote in message
<f78fsa$33e$1(a)fred.mathworks.com>...
> Dear All,
>
> I have been reading the post of Adaptive Filtering Demos
posted by Ricardo Losada in the Signal Processing File
exchange section of this site.
> Please excuse my ignorance of Matlab language structure,
but I was wondering if anyone could show how and where to
substitute the randomly generated noise for a .wav file of
noise I have.
> I would be interested to see how the algorithm performs
under varying types of noise files, but unsure which
sections of code I can remove and substitute in my .wav
file.
> Below is the algorithm as posted by Ricardo Losada
(although I believe originated by Scott Douglas).
>
> >>>>>>>>>>>>>>>>>>>>>>>>>
> %The Secondary Propagation Path
> Fs = 8000;
> N = 800;
> delayS = 7;
> Fd = fdesign.bandpass('N,Fst1,Fst2,Ast',8,0.04,0.5,20);
> Hd = design(Fd,'cheby2','FilterStructure','df2tsos');
> H = filter(Hd,[zeros(1,delayS) log(0.99*rand(1,N-delayS)
+0.01).* ...
> sign(randn(1,N-delayS)).*exp(-0.01*(1:N-delayS))]);
> H = H/norm(H);
> t = 1/Fs:1/Fs:N/Fs;
> plot(t,H,'b');
> xlabel('Time [sec]');
> ylabel('Coefficient value');
> title('True Secondary Path Impulse Response');
>
> %% Estimating the Secondary Propagation Path
> ntrS = 30000;
> s = randn(1,ntrS);
> dS = filter(H,1,s) + 0.01*randn(1,ntrS);
>
> %% Designing the Secondary Propagation Path Estimate
> M = 250;
> muS = 0.1; offsetS = 0.1;
> h = adaptfilt.nlms(M,muS,1,offsetS);
> [yS,eS] = filter(h,s,dS);
>
> n = 1:ntrS;
> plot(n,dS,n,yS,n,eS);
>
>
> xlabel('Number of iterations');
> ylabel('Signal value');
> title('Secondary Identification Using the NLMS Adaptive
Filter');
> legend('Desired Signal','Output Signal','Error Signal');
>
>
> %% Accuracy of the Secondary Path Estimate
> Hhat = h.Coefficients;
> plot(t,H,t(1:M),Hhat,t,[H(1:M)-Hhat(1:M) H(M+1:N)]);
> xlabel('Time [sec]');
> ylabel('Coefficient value');
> title('Secondary Path Impulse Response Estimation');
> legend('True','Estimated','Error');
>
>
> %% The Primary Propagation Path
> delayW = 15;
> Fd2 = fdesign.bandpass('N,Fst1,Fst2,Ast',10,0.05,0.2,20);
> Hd2 = design(Fd2,'cheby2','FilterStructure','df2tsos');
> G = filter(Hd2,[zeros(1,delayW) log(0.99*rand(1,N-delayW)
+0.01).*...
> sign(randn(1,N-delayW)).*exp(-0.01*(1:N-delayW))]);
> G = G/norm(G);
> plot(t,G,'b');
> xlabel('Time [sec]');
> ylabel('Coefficient value');
> title('Primary Path Impulse Response');
>
>
> %% The Noise to be Cancelled
> ntrW = 60000;
> F0 = 60;
> n = 1:ntrW;
> A = [0.01 0.01 0.02 0.2 0.3 0.4 0.3 0.2 0.1 0.07 0.02
0.01];
> x = zeros(1,ntrW);
> for k=1:length(A);
> x = x + A(k)*sin(2*pi*(F0*k/Fs*n+rand(1)));
> end
> d = filter(G,1,x) + 0.1*randn(1,ntrW);
> Hp = spectrum.welch; Hp.SegmentLength = 4444;
> Hp.FFTLength='UserDefined';
> Pd = psd(Hp,d(ntrW-20000:ntrW),'NFFT',8192,'Fs',Fs);
> plot(Pd)
> axis([0 2 -70 0]);
> title('Power Spectral Density of the Noise to be
Cancelled');
> p8K = audioplayer(d/max(abs(d)),Fs);
> playblocking(p8K);
>
>
> %% Active Noise Control using the filtered-X LMS Algorithm
> xhat = x + 0.1*randn(1,ntrW);
> L = 350;
> muW = 0.0001;
> h = adaptfilt.filtxlms(L,muW,1,Hhat);
> [y,e] = filter(h,xhat,d);
>
> plot(n,d,'b',n,y,'g',n,e,'r');
> xlabel('Number of iterations');
> ylabel('Signal value');
> tstr = ['Active Noise Control Using', ...
> ' the Filtered-X LMS Adaptive Controller'];
> title(tstr);
> legend('Original Noise','Anti-Noise','Residual Noise');
> p8K = audioplayer(e/max(abs(e)),Fs);
> playblocking(p8K);
>
> %% Residual Error Signal Spectrum
> Pe = psd(Hp,e(ntrW-20000:ntrW),'NFFT',8192,'Fs',Fs);
> plot(Pd.Frequencies,10*log10(Pd.Data(:,1)),'b',...
> Pe.Frequencies,10*log10(Pe.Data(:,1)),'r');
> axis([0 2000 -70 0]);
> grid on
> xlabel('Frequency (Hz)');
> ylabel('Power/frequency (dB/Hz)');
> tstr = ['Power Spectral Density of the', ...
> ' Original and Attenuated Noise'];
> title(tstr);
> legend('Original','Attenuated');
>
>
> Any help would be greatly appreciated and please accept
my apologies for my lack of understanding!
>
> Thanks in advance
>
> Regards,
>
> Kevin.
>
>
>

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