NDLI: Minimum variance spectral estimator fast algorithms based on covariance and modified covariance methods of linear prediction

Content Provider	IEEE Xplore Digital Library
Author	Marple Jr., S.L.
Copyright Year	2001
Description	Author affiliation: ORINCON, San Diego, CA, USA (Marple, S.L., Jr.)
Abstract	The usual formulation of the minimum variance spectral estimator (MVSE) depends on the inverse of the autocorrelation matrix, which has a Toeplitz structure in the 1D case and a doubly-block-Toeplitz structure in the 2D case. These inverses can be formulated in terms of triangular Toeplitz or block-triangular-Toeplitz matrix products which, when substituted into the MVSE formula, yield fast computational formulations for the 1D and 2D MUSE. This paper extends the class of 1D fast MUSE algorithms to the case of least squares data-only covariance and modified covariance formulations, which involve near-to-Toeplitz matrix inverses that also have special representations as products of triangular Toeplitz matrices. Due to space limitations, a future paper will provide the 1D MVSE versions.
Starting Page	711
Ending Page	714
File Size	312227
Page Count	4
File Format	PDF
ISBN	078037147X
ISSN	10586393
DOI	10.1109/ACSSC.2001.987016
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2001-11-04
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Covariance matrix Autocorrelation Matrices Finite impulse response filter Least squares methods Signal processing algorithms Filtering Signal processing Frequency
Content Type	Text
Resource Type	Article
Subject	Signal Processing Computer Networks and Communications

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