Using the cpsd function

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Eric
Eric on 15 Jan 2021
Commented: Bjorn Gustavsson on 15 Jan 2021
Dear everyone,
I have some data that was collected at a sampling rate of 200 sample/second. However, I want to calculated the cross-spectral density for only 20 sample (or 100 ms). Does anyone know how to use the cpsd function from MATLAB to do this?
So far, I have made this my input:
[Pxy,W] = cpsd(xdata,ydata,[],10,[],0);
But this gives me a weird values as output.
Any help is much appreciated!
Best,
Eric

Answers (1)

Bjorn Gustavsson
Bjorn Gustavsson on 15 Jan 2021
Simply use the spectrogram function to calculate the spectrograms of your two time-series, something like this:
[S1,F1,T1] = spectrogram(D1,Window,Noverlap,[],Fs);
[S2,F2,T2] = spectrogram(D2,Window,Noverlap,[],Fs);
C12 = S1.*conj(S2);
xp12 = abs(C12);
That should give you the complex cross-spectra and the cross-spectral power.
20 samples are not that very many though? You might not get that great frequency-resolution on that...
HTH
  2 Comments
Eric
Eric on 15 Jan 2021
Thanks for the comment!
What would you set the window length and overlap to if you want to calculate the cross-spectral density for smaller segments independently of each other?
Best,
Eric
Bjorn Gustavsson
Bjorn Gustavsson on 15 Jan 2021
You're welcome.
That is a great question - In my experience it comes down to what time and frequency-resolution you need, and the time-variations of your signal. I typically test around a bit. In most of my cases I have interest in variations that occur on "time-scales" of some 32-100 samples, for which I typically use 48 - 150 samples and 16 - 50 sample overlap, and then I live with the spectral resolution that gives me. With hanning/hamming/blackman/etc windows the samples shouldn't be too correlated. (note that this is not my field of expertise - then I'd start to talk about multi-taper something-slepian-something-advanced - but this is what I've gotten good enough results with.)

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