Maximum Likelihood-Based Recursive Least-Squares Algorithm for Multivariable Systems with Colored Noises Using the Decomposition Technique

This paper considers the parameter estimation problems for a class of multivariable equation-error systems with colored noises. By using the decomposition technique, a multivariable system is transformed into several subsystems to reduce the computational burden, and a maximum likelihood-based recur...

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Bibliographic Details
Published in:Circuits, systems, and signal processing systems, and signal processing, 2019-03, Vol.38 (3), p.986-1004
Main Authors: Xia, Huafeng, Ji, Yan, Xu, Ling, Hayat, Tasawar
Format: Article
Language:English
Subjects:
Algorithms
Circuits and Systems
Computation
Computer simulation
Decomposition
Electrical Engineering
Electronics and Microelectronics
Engineering
Instrumentation
Least squares
Parameter estimation
Parameter identification
Signal,Image and Speech Processing
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Summary:This paper considers the parameter estimation problems for a class of multivariable equation-error systems with colored noises. By using the decomposition technique, a multivariable system is transformed into several subsystems to reduce the computational burden, and a maximum likelihood-based recursive least-squares identification algorithm is developed for estimating the parameters of each subsystem. As a comparison, a multivariable recursive extended least-squares algorithm is presented. The analysis indicates that the proposed algorithm has lower computational complexity than the multivariable recursive extended least-squares algorithm, and the numerical simulation results demonstrate that the proposed method is effective.
ISSN:0278-081X
1531-5878
DOI:10.1007/s00034-018-0904-7