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Power spectral density of gaussian white noise

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TheBeginner on 8 Nov 2013
Answered: Jeremy on 18 Jun 2015
Hi, I just wanted to check that the matlab function "pwelch" gives a correct estimates of the PSD of a gaussian white noise. I plot the estimate of the PSD and also the variance, which is supposed to be equal to the mean of PSD. I always have a bias that I don't understand.
Here's my code :
sigma = 1000;
L = 200000;
noise= randn(1,L) * sigma;
[PSD_noise,vect_freq_noise] = pwelch(noise,75000,[],4000);
plot(vect_freq_noise,2*PSD_noise,'-g'), %PSD
%Theoritical value of the PSD
hold on, plot([vect_freq_noise(1) vect_freq_noise(end)],[sigma^2 sigma^2],'r');
%Value of the mean
plot([vect_freq_noise(1) vect_freq_noise(end)],[mean(2*PSD_noise) mean(2*PSD_noise)],'b');
Any idea where's the mistake?
Thank you

  1 Comment

TheBeginner on 8 Nov 2013
I have also tried to calculate myself the PSD :
sigma = 1000;
L = 200000;
noise= randn(1,L) * sigma;
PSD = abs(fft(noise)).^2/length(noise);
vect_freq = linspace(0,pi,length(PSD));
hold on, plot([vect_freq(1) vect_freq(end)],[sigma^2 sigma^2],'r');
hold on, plot([vect_freq(1) vect_freq(end)],[mean(PSD) mean(PSD)],'-.b');
And it works fine. I think there's a normalization factor in pwelch that I can't quite figure out.

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Answers (1)

Jeremy on 18 Jun 2015
The "density" in PSD means that the power is normalized to something, usually 1 Hz, but in this case it is the Nyquist frequewncy since there was sampling rate input into pwelch. The energy of white noise will be spread over all frequencies so you need to look at the integral of the signal:
sum(PSD_noise*.0016) % this should equal omega^2


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