
Re: random timeseries displacement data from PSD and back again
Posted:
Jun 24, 2013 9:01 PM


On Tuesday, June 25, 2013 10:31:16 AM UTC+12, Jim Schwendeman wrote: > TideMan, > > > > Maybe the better question is this: > > > > When I create my timeseries data, how do I know that it's scaled correctly? When I replicated the complex conjugate prior to the ifft, I doubled the number of points, so I guess I'm not entirely sure. > > > > I believe I am correct, because if I do the sum(abs(y).^2), that is equal to the mean g^2/Hz from the original PSD, which leads me to believe I've satisfied Parseval's theorem. > > > > Thoughts?
I can't follow your code. You seem to define PSD as ones, then use it as if it had data. I gave up.............
This is Parseval's Law: sum(PSD)*df must equal var(y) The area under the spectrum must be the variance of the time signal. In your case, I think df is 1.

