Path: utzoo!utgpu!jarvis.csri.toronto.edu!mailrus!cs.utexas.edu!uwm.edu!mrsvr.UUCP!kohli@gemed.ge.com
From: kohli@gemed (Jim Kohli)
Newsgroups: comp.dsp
Subject: eigenanalysis-based frequency estimation
Message-ID: <1769@mrsvr.UUCP>
Date: 27 Dec 89 22:47:40 GMT
Sender: news@mrsvr.UUCP
Reply-To: kohli@gemed.ge.com (Jim Kohli)
Organization: Geo-Duckside Exploration Unit # 1
Lines: 24


I've been attempting to use the routines in Marple's "Digital
Spectral Analysis with applications" (a VERY fine book), but
I'm having some problem coming up with a "rule of thumb" for
automagically assigning a value for IP, the "dimension of data
matrix" parameter, in the EIGENFREQ routine.  This parameter
represents the rank of the sample autocorrelation matrix.

Can someone tell me what the rationale is for not making this
parameter the same dimension as the data being operated on?
(other than reducing the amount of computations-- and if
that is why, some criteria for determination of a good rule
of thumb???).

In Marple's example on 64 points of test data, the signal
space dimension is set to be 11, but IP is 15 (as opposed
to 64).

thanks (as usual!),

Jim Kohli

GE Medical Systems
Waukesha WI, USA