DocumentCode
1180748
Title
Decomposed predictive transform estimation
Author
Feria, Erlan H.
Author_Institution
Coll. of Staten Island, City Univ. of New York, NY, USA
Volume
42
Issue
10
fYear
1994
fDate
10/1/1994 12:00:00 AM
Firstpage
2811
Lastpage
2822
Abstract
A novel design and implementation decompositions are found to arise for a minimum mean squared error (MMSE) linear predictive transform (LPT) estimator when certain symmetry conditions are satisfied by the first- and second-order statistics used to design the estimator. This results in a decomposed LPT estimator whose design and implementation computational effort is significantly less than that of the original estimator
Keywords
digital circuits; encoding; image processing; least squares approximations; linear predictive coding; matrix algebra; parameter estimation; signal processing; statistics; transforms; computational effort; decomposed predictive transform estimation; design; first-order statistics; implementation decompositions; linear predictive transform; minimum mean squared error; second-order statistics; symmetry conditions; Communication system control; Decoding; Equations; Kalman filters; Multidimensional systems; Process control; Signal design; Signal processing; Source coding; State-space methods;
fLanguage
English
Journal_Title
Signal Processing, IEEE Transactions on
Publisher
ieee
ISSN
1053-587X
Type
jour
DOI
10.1109/78.324745
Filename
324745
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