Two-stage recursive least squares parameter estimation algorithm for output error models

This paper presents a two-stage recursive least squares algorithm for output error models. The basic idea is to combine the auxiliary model identification idea and the decomposition technique and to decompose a system into two subsystems, which contain one parameter vector each. Compared with the au...

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Bibliographic Details
Published in:Mathematical and computer modelling Vol. 55; no. 3; pp. 1151 - 1159
Main Authors: Duan, Honghong, Jia, Jie, Ding, Ruifeng
Format: Journal Article
Language:English
Published: Elsevier Ltd 01.02.2012
Subjects:
algorithms
Auxiliary model
Decomposition technique
Least squares
Two-stage algorithm
Decomposition technique
Auxiliary model
Least squares
Two-stage algorithm
ISSN:0895-7177, 1872-9479
Online Access:Get full text
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Summary:This paper presents a two-stage recursive least squares algorithm for output error models. The basic idea is to combine the auxiliary model identification idea and the decomposition technique and to decompose a system into two subsystems, which contain one parameter vector each. Compared with the auxiliary model based recursive least squares algorithm, the proposed algorithm has less computational burden.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
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content type line 23
ISSN:0895-7177
1872-9479
DOI:10.1016/j.mcm.2011.09.039