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From: Lucila on 12 Aug 2010 07:14
Hello,
I am generating a random process by passing white noise throught a second order system.
a/(s^2+2*z*wn*s+wn^2)
The autocorrelation function calculated using xcorr gives me what I expected, but the psd (calculated using fft) does not.
I expected to see a decreasing line with slope -4 (loglog-Plot)
If I increase the number of samples or the magnitude of the natural frequency (wn), I can see the correct slope.
Why?
Thank you and Regards,
Lucy
From: Wayne King on 12 Aug 2010 07:24
"Lucila " <lucpatrod(a)gmail.com> wrote in message <i40l1t$god$1(a)fred.mathworks.com>...
> Hello,
> I am generating a random process by passing white noise throught a second order system.
> a/(s^2+2*z*wn*s+wn^2)
> The autocorrelation function calculated using xcorr gives me what I expected, but the psd (calculated using fft) does not.
> I expected to see a decreasing line with slope -4 (loglog-Plot)
> If I increase the number of samples or the magnitude of the natural frequency (wn), I can see the correct slope.
> Why?
> Thank you and Regards,
> Lucy

Hi Lucy, see my response in your other post.
Wayne
From: sudipta pramanik on 12 Aug 2010 09:32
sir, I have two psd which are certainly different.Give a parameter by which i can distinctly identify them

From: Lucila on 12 Aug 2010 11:27
Hello,
Thank you for the answer.
The code:

nData=1e5;
n=randn(1,nData); % Input signal
Fs = 200; %Hz
zeros_plano_S = [];
polos_plano_S = [-0.01+0.003i -0.01-0.003i]; %

[b,a] = zp2tf(zeros_plano_S,polos_plano_S,1); %
[numd,dend] = impinvar(b,a,Fs);
N2 = filter(numd,dend,n);

[Pxx,freq]=pwelch(N2,[],[],[],Fs);
figure; loglog(freq,Pxx);

if nData=1e5 the most predominant slope is -2.
if nData=1e7 the most predominant slope is -4.
I want to know why, it seem to be in relationship with the number of data and the location of the poles?

Thanks
From: Lucila on 12 Aug 2010 11:45
Hello,
Thank you for the answer.
The code:

nData=1e5;
n=randn(1,nData); % Input signal
Fs = 200; %Hz
zeros_plano_S = [];
polos_plano_S = [-0.01+0.003i -0.01-0.003i]; %

[b,a] = zp2tf(zeros_plano_S,polos_plano_S,1); %
[numd,dend] = impinvar(b,a,Fs);
N2 = filter(numd,dend,n);

[Pxx,freq]=pwelch(N2,[],[],[],Fs);
figure; loglog(freq,Pxx);

if nData=1e5 the most predominant slope is -2.
if nData=1e7 the most predominant slope is -4.
I want to know why, it seem to be in relationship with the number of data and the location of the poles?

Thanks
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