Auxiliary Variable-Based Identification Algorithms for Uncertain-Input Models

This study presents two auxiliary variable-based identification algorithms for uncertain-input models. The auxiliary variable-based least squares algorithm can obtain unbiased parameter estimates by introducing suitable auxiliary variable vectors. Furthermore, an auxiliary variable-based recursive l...

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Bibliographic Details
Published in:Circuits, systems, and signal processing Vol. 39; no. 7; pp. 3389 - 3404
Main Authors: Chen, Jing, Zhu, Quanmin, Chandra, Budi, Pu, Yan
Format: Journal Article
Language:English
Published: New York Springer US 01.07.2020
Springer Nature B.V
Subjects:
Algorithms
Circuits and Systems
Computer simulation
Electrical Engineering
Electronics and Microelectronics
Engineering
Instrumentation
Least squares
Parameter estimation
Signal,Image and Speech Processing
Unbiased parameter estimate
Uncertain-input model
Computational effort
Auxiliary variable
Least squares algorithm
ISSN:0278-081X, 1531-5878
Online Access:Get full text
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Summary:This study presents two auxiliary variable-based identification algorithms for uncertain-input models. The auxiliary variable-based least squares algorithm can obtain unbiased parameter estimates by introducing suitable auxiliary variable vectors. Furthermore, an auxiliary variable-based recursive least squares algorithm is proposed to reduce the computational efforts. To validate the framework and algorithms developed, it has conducted a series of bench tests with computational experiments. The simulated numerical results/plots are consistent with the analytically derived results in terms of the feasibility and effectiveness of the proposed procedure.
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ISSN:0278-081X
1531-5878
DOI:10.1007/s00034-019-01320-w