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Article #536Re: FFT vs ARMA (was FFTs of Low Frequency Signals (really: decimation))
From: Ashok C. Popat
Date: Wed, 22 Nov 1989 17:08
Date: Wed, 22 Nov 1989 17:08
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1466 bytes
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
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Path: arc1-ca.pugleaf.net!utzoo!utgpu!jarvis.csri.toronto.edu!mailrus!uwm.edu!gem.mps.ohio-state.edu!tut.cis.ohio-state.edu!ucbvax!bloom-beacon!atrp.mit.edu!ashok 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 References: <5619@videovax.tv.tek.com> <10208@cadnetix.COM> <2586@irit.oakhill.UUCP> <5305@orca.WV.TEK.COM> <5622@videovax.tv.tek.com> <98204@ti-csl.csc.ti.com> <5630@videovax.tv.tek.com> <98990@ti-csl.csc.ti.com> Sender: news@athena.mit.edu (News system) Reply-To: ashok@atrp.mit.edu (Ashok C. Popat) Organization: MIT Lines: 17