DocumentCode
1280099
Title
Threshold bounds in SVD and a new iterative algorithm for order selection in AR models
Author
Konstantinides, Konstantinos
Author_Institution
Hewlett-Packard Lab., Palo Alto, CA, USA
Volume
39
Issue
5
fYear
1991
fDate
5/1/1991 12:00:00 AM
Firstpage
1218
Lastpage
1221
Abstract
The problem of order determination of AR (autoregressive) models using singular value decomposition (SVD) is reexamined from a statistical point of view. Thresholds for distinguishing between significant and nonsignificant singular values are derived, and a novel iterative algorithm for order selection in AR models is presented. Simulation results show the technique to be very effective when a small number of samples is available
Keywords
iterative methods; matrix algebra; statistics; AR models; autoregressive models; iterative algorithm; order determination; simulation results; singular value decomposition; statistics; threshold bounds; Apertures; Array signal processing; Iterative algorithms; Maximum likelihood detection; Maximum likelihood estimation; Optical signal processing; Parameter estimation; Sensor arrays; Signal processing; Speech processing;
fLanguage
English
Journal_Title
Signal Processing, IEEE Transactions on
Publisher
ieee
ISSN
1053-587X
Type
jour
DOI
10.1109/78.80960
Filename
80960
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