On Fri, 26 Feb 2010 16:32:01 -0500 Anne Archibald <peridot.faceted@gmail.com> wrote:
Hi,
Looking at a periodic signal buried in noise is a well-studied problem, with many techniques for attacking it. You really need to be a little more specific about what you want to do. For example, is your input signal really a sinusoid, or does it have harmonic content? Are you trying to detect a weak periodic signal or are you trying to extract the features of a strong periodic signal? Is your signal exactly periodic, does it have some (deterministic or random) wander, or are you looking for the power spectrum of a broadband signal?
If your input data are non-uniformly sampled, everything becomes more difficult (and computationally expensive), but there are solutions (e.g. the Lomb-Scargle periodogram).
Anne
Hi Anne, Thank you very much for your hints ! BTW, a BSD licensed code for the Lomb-Scargle periodogram is available at http://www.mathworks.com/matlabcentral/fileexchange/993-lombscargle-m http://www.mathworks.com/matlabcentral/fileexchange/20004-lomb-lomb-scargle-... I am newbie to signal processing. Is there a good introduction that you can recommend ? There are so many books on signal processing. It should cover engineering applications. What makes a signal weak/strong periodic ? The signals come from real-life application (pressure / acceleration data). Do I need a filter before I apply FFT ? What would you do if you know nothing about the origin of the signal ? How can I distinguish between deterministic and random wander ? Cheers, Nils