# check power spectrum

my question is quite straight-forward to be grasped and handled.

I have an 1D array, F_11 representing a target power spectrum. It is sketched in the following figure Then, I start generating a time series u which embodies the properties of F_11, as follows

nn = complex(normrnd(0,1,[1,1000]),normrnd(0,1,[1,1000]));
u = abs(fftn(fftshift(F_11.*nn)));


Finally, just to check that u does actually reproduce a spectrum as F_11, I try going backwards as follows

ps =  abs(ifftn(ifftshift(u)));


But, when plotting ps, it does not exactly match F_11 In the high frequency area, ps drifts upwards, which is quite weird.

Would you mind to sketch the flaw in my procedure?

Your u variable is just the magnitude of the FFT, not the actual complex numbers that represent the FFT. Try removing the abs() from u and then doing the IFFT.
• Do you mean calling u = (fftn(fftshift(F_11.*nn))); and ps = abs(ifftn(ifftshift(u)));? – fpe Jan 24 '13 at 17:19
• Yes. You can keep u in its complex number form and then call abs() or angle() on it before plotting depending on if you want to see the magnitude or the phase of the FFT. – user1860611 Jan 24 '13 at 17:51
• The power spectrum is the magnitude squared of the FFT. Normally I would take a time signal x and have X=fft(x), then ps=abs(X).^2=X*X', but to get back to x I would do x=ifft(X) not x=ifft(ps) I don't think your u is a time series. – user1860611 Jan 24 '13 at 18:35
Can you first generate white noise and then filter it with the power spectrum that you desire? You can generate white Gaussian noise using wgn1.