DocumentCode
1441099
Title
Structural stability of least squares prediction methods
Author
Idier, Jérôme ; Giovannelli, Jean-François
Author_Institution
Lab. des Signaux et Syst., Supelec, Gif-sur-Yvette, France
Volume
46
Issue
11
fYear
1998
fDate
11/1/1998 12:00:00 AM
Firstpage
3109
Lastpage
3111
Abstract
A structural stability condition is sought for least squares linear prediction methods in the given data case. Save the Toeplitz case, the structure of the normal equation matrix yields no acknowledged guarantee of stability. Here, a new sufficient condition is provided, and several least squares prediction methods are shown to be structurally stable
Keywords
filtering theory; least squares approximations; matrix algebra; prediction theory; stability; Toeplitz matrix; displacement matrix; least squares linear prediction methods; linear prediction filters; normal equation matrix; positive semidefinite matrix; structural stability condition; sufficient condition; Autocorrelation; Equations; Filters; Least squares methods; Prediction methods; Robustness; Stability; Statistical distributions; Structural engineering; Sufficient conditions;
fLanguage
English
Journal_Title
Signal Processing, IEEE Transactions on
Publisher
ieee
ISSN
1053-587X
Type
jour
DOI
10.1109/78.726826
Filename
726826
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