function noise=noisecg(N,a1,a2)%NOISECG Analytic complex gaussian noise.%	NOISE=NOISECG(N,A1,A2) computes an analytic complex gaussian%	noise of length N with mean 0.0 and variance 1.0. %%	NOISE=NOISECG(N) yields a complex white gaussian noise.%%	NOISE=NOISECG(N,A1) yields a complex colored gaussian noise%	obtained by filtering a white gaussian noise through a%		sqrt(1-A1^2)/(1-A1*z^(-1)) %	first order filter.%%	NOISE=NOISECG(N,A1,A2) yields a complex colored gaussian noise%	obtained by filtering a white gaussian noise through a%		sqrt(1-A1^2-A2^2)/(1-A1*z^(-1)-A2*z^(-2)) %	second order filter.%%	Example :%	 N=512;noise=noisecg(N);mean(noise),std(noise).^2%	 subplot(211); plot(real(noise)); axis([1 N -3 3]);%	 subplot(212); f=linspace(-0.5,0.5,N); %	 plot(f,abs(fftshift(fft(noise))).^2);%		%	See also RAND, RANDN, NOISECU.%	O. Lemoine, June 95/May 96 - F. Auger, August 95.%	Copyright (c) 1996 by CNRS (France).%%	------------------- CONFIDENTIAL PROGRAM -------------------- %	This program can not be used without the authorization of its%	author(s). For any comment or bug report, please send e-mail to %	f.auger@ieee.org if (N <= 0), error ('The signal length N must be strictly positive' );end;if (nargin==1), if N<=2,  noise=(randn(N,1)+j*randn(N,1))/sqrt(2);  else  noise=randn(2^nextpow2(N),1);  endelseif (nargin==2), if (abs(a1)>=1.0),  error ('for a first order filter, abs(a1) must be strictly lower than 1'); elseif (abs(a1)<=eps),  if N<=2,   noise=(randn(N,1)+j*randn(N,1))/sqrt(2);   else   noise=randn(N,1);  end else  if N<=2,   noise=(randn(N,1)+j*randn(N,1))/sqrt(2);   else   Nnoise=ceil(N-2.0/log(a1));   noise=randn(2^nextpow2(Nnoise),1);  end  noise=filter(sqrt(1.0-a1^2), [1 -a1],noise); end;elseif (nargin==3), if any(roots([1 -a1 -a2])>1),  error('unstable filter'); else  if N<=2,   noise=(randn(N,1)+j*randn(N,1))/sqrt(2);   else   Nnoise=ceil(N-2.0/log(max(roots([1 -a1 -a2]))));   noise=randn(2^nextpow2(Nnoise),1);  end  noise=filter(sqrt(1.0-a1^2-a2^2), [1 -a1 -a2],noise); end;end;if N>2, noise=hilbert(noise)/std(noise)/sqrt(2); noise=noise(length(noise)-(N-1:-1:0));end