DocumentCode
978607
Title
Stability of multivariable least-squares models
Author
Regalia, Phillip A. ; Stoica, Petre
Author_Institution
Dept. Signal et Image, Inst. Nat. des Telecommun., Evry, France
Volume
2
Issue
10
fYear
1995
Firstpage
195
Lastpage
196
Abstract
Least-squares equation-error models are widely used as a simple means of estimating an input-output transfer function in a system identification context.. Although the models furnished by the least-squares method are not always stable, some recent works have shown that an autoregressive constraint on the input is sufficient to ensure stability of the furnished model. Here we provide a simple proof of this property for multivariable system estimation.<>
Keywords
autoregressive processes; error analysis; estimation theory; identification; least mean squares methods; multivariable systems; numerical stability; transfer functions; autoregressive constraint; input-output transfer function; least-squares equation-error model; least-squares method; multivariable least-squares models; multivariable system estimation; stability; system identification; Autoregressive processes; Context modeling; Covariance matrix; Equations; MIMO; Polynomials; Stability; System identification; Transfer functions; White noise;
fLanguage
English
Journal_Title
Signal Processing Letters, IEEE
Publisher
ieee
ISSN
1070-9908
Type
jour
DOI
10.1109/97.466708
Filename
466708
Link To Document