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📄 music.m

📁 solution for the Statistical modelling for digital signal processing by hayes
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function Px = music(x,p,M)%MUSIC	Frequency estimation using the MUSIC algorithm.%-----%USAGE	Px=music(x,p,M)%%	The input sequence x is assumed to consist of p complex%	exponentials in white noise.  The frequencies of the%	complex exponentials and the variance of the white noise%	are estimated using the MUSIC algorithm.  %%	x : input sequence%       p : number of complex exponentials to find%	M : number of noise eigenvectors to use%%	The frequency estimates are found from the peaks of the%	pseudospectrum Px.%%  see also PHD, EV, and MIN_NORM%%---------------------------------------------------------------% copyright 1996, by M.H. Hayes.  For use with the book % "Statistical Digital Signal Processing and Modeling"% (John Wiley & Sons, 1996).%---------------------------------------------------------------   x   = x(:);   if M<p+1 | length(x)<M, error('Size of R is inappropriate'), end   R = covar(x,M);   [v,d]=eig(R);   [y,i]=sort(diag(d));   Px=0;   for j=1:M-p       Px=Px+abs(fft(v(:,i(j)),1024));       end;   Px=-20*log10(Px);   end;

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