Why does periodogram varies with data length?
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Hello,
I'm trying to understand better how periodogram works by using it with pure sinusoids.
Fs = 1000;
t = 0:1/Fs:1-1/Fs;
x = sin(2*pi*100*t);
[psdestx,Fxx] = periodogram(x,[],length(x),Fs);
plot(Fxx,psdestx); grid on;
xlabel('Hz');
title('Periodogram Power Spectral Density Estimate');
I took most of the above code from a MATLAB example in the documentation center: http://www.mathworks.com/help/signal/ug/psd-estimate-using-fft.html
The response, 0.5 peak at 100 Hz, seems correct to me, since the theoretical average power of a sinusoid is (A^2)/2. It's also the same answer I get when I type:
mean(x.^2)
My doubt arises when I increase data length, from the code's second line:
t = 0:1/Fs:2-1/Fs;
Why does this change my PSD estimate? Since I'm dealing with a periodic signal, shouldn't the average power remains constant, despite data length?
Thank you, Vinícius
Accepted Answer
More Answers (3)
Vinicius
on 14 Oct 2013
0 votes
Wayne King
on 14 Oct 2013
In R2012a, you can use spectrum.periodogram and then msspectrum
Fs = 1000;
t = 0:1/Fs:2-1/Fs;
x = 0.5*cos(2*pi*100*t)+2*sin(2*pi*200*t);
hper = spectrum.periodogram;
hper.Windowname = 'Flat top';
hms = msspectrum(hper,x,'Fs',Fs);
plot(hms.Frequencies,hms.Data)
Looking at the plot (this is a one-sided power spectrum), the intepretation is this, the power at 100 Hz is 0.125 so you have a cosine (ignoring phase) with an amplitude of
sqrt(2*0.125)
The power estimate at 200 Hz is 2 so you have a sinusoid with an amplitude of
sqrt(2*2)
Vinicius
on 14 Oct 2013
0 votes
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