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From: ashok@atrp.mit.edu (Ashok C. Popat)
Newsgroups: comp.dsp
Subject: Re: FFT vs ARMA (was FFTs of Low Frequency Signals (really: decimation))
Message-ID: <1989Nov22.170850.21777@athena.mit.edu>
Date: 22 Nov 89 17:08:50 GMT
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In article <98990@ti-csl.csc.ti.com> oh@m2.UUCP (Stephen Oh) writes:
>
>Again, for the resolutions of PSD, parametric approches are *ALOT* better than
>FFT-based PSD.
>

In applications, you don't always have a good apriori formal model.
Unless you have a formal model that's *useful* for your application,
parametric estimation is worthless.

Suppose I gave you some data (say 10^6 samples) and told you that the
source was ergodic, but nothing else.  How would you estimate the
spectrum?  If you used an ARMA model, how would you decide what the
order of the model should be?  Wouldn't you have much more confidence
in an averaged-periodogram (i.e., DFT-based) estimate?  I would.

Ashok Chhabedia Popat  MIT Rm 36-665  (617) 253-7302