att...@kinali.ch said: > FFT based systems take a white, normal distributed noise source, Fourier > transform it, filter it in frequency domain and transform it back. Runtime is > dominated by the FFT and thus O(n*log(n)). There was a nice paper by either > Barnes or Greenhall (or both?) on this, which I seem currently unable to > find. This is also the method employed by the bruiteur tool from sigma-theta.
> Biggest disadvantage of this method is, that it operates on the whole sample > length multiple times. I.e it becomes slow very quickly, especially when the > whole sample length is larger than main memory. But they deliver exact > results with exactly the spectrum / time-correlation you want. What sort of times and memory are interesting? You can rent a cloud server with a few hundred gigabytes of memory for a few $/hour. -- These are my opinions. I hate spam. _______________________________________________ time-nuts mailing list -- time-nuts@lists.febo.com -- To unsubscribe send an email to time-nuts-le...@lists.febo.com To unsubscribe, go to and follow the instructions there.