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- Title
Convergence of the recursive identification algorithms for multivariate pseudo-linear regressive systems.
- Authors
Wang, Xuehai; Ding, Feng
- Abstract
The performance analysis of the recursive algorithms for the multivariate systems with an autoregressive moving average noise process is still open. This paper analyzes the convergence of two recursive identification algorithms, the multivariate recursive generalized extended least squares algorithm and the multivariate generalized extended stochastic gradient algorithm, for pseudo-linear multivariate systems and proves that the parameter estimation errors consistently converge to zero under persistent excitation conditions. The simulation results show that the proposed algorithms work well. Copyright © 2015 John Wiley & Sons, Ltd.
- Subjects
LEAST squares; PARAMETER estimation; DYNAMICAL systems; MARTINGALES (Mathematics); SIGNAL processing
- Publication
International Journal of Adaptive Control & Signal Processing, 2016, Vol 30, Issue 6, p824
- ISSN
0890-6327
- Publication type
Article
- DOI
10.1002/acs.2642