DocumentCode
854178
Title
Strong consistency of ML estimators using partial fraction and elementary subsystem representation of multivariable systems
Author
Keviczky, László ; Bokor, Jozsef ; Veres, Sándor
Author_Institution
Hungarian Academy of Sciences, Budapest, Hungary
Volume
32
Issue
10
fYear
1987
fDate
10/1/1987 12:00:00 AM
Firstpage
867
Lastpage
876
Abstract
The strong consistency of ML estimators for partial fraction matrix (PFM) and elementary subsystem (ESS) representations of vector ARMA processes will be discussed for the case when the structure is overestimated. The main results of the paper are the off-line strong consistency theorems of ML estimators for PFM representation, when the number of poles is overestimated and for the ESS representations when the number of ESS´s associated with the poles is overestimated.
Keywords
Autoregressive moving-average processes; Partial fraction expansions; Transfer function matrices; maximum-likelihood (ML) estimation; Convergence; Electronic switching systems; Estimation theory; Gaussian processes; MIMO; Maximum likelihood estimation; Parameter estimation; Stability; Transfer functions; White noise;
fLanguage
English
Journal_Title
Automatic Control, IEEE Transactions on
Publisher
ieee
ISSN
0018-9286
Type
jour
DOI
10.1109/TAC.1987.1104465
Filename
1104465
Link To Document