Convergence of the auxiliary model-based multi-innovation generalized extended stochastic gradient algorithm for Box–Jenkins systems

This paper focuses on the parameter estimation problem of Box–Jenkins systems. Using the multi-innovation identification theory, an auxiliary model-based multi-innovation generalized extended stochastic gradient algorithm is derived. The convergence of the proposed algorithm is analyzed based on the...

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Bibliographic Details
Published in:	Nonlinear dynamics Vol. 82; no. 1-2; pp. 269 - 280
Main Authors:	Wang, Xuehai, Ding, Feng
Format:	Journal Article
Language:	English
Published:	Dordrecht Springer Netherlands 01.10.2015 Springer Nature B.V
Subjects:	Algorithms Automotive Engineering Classical Mechanics Computer simulation Control Convergence Dynamical Systems Economic models Engineering Estimating techniques Innovations Martingales Mathematical models Mechanical Engineering Original Paper Parameter estimation Parameter identification Vibration Box–Jenkins system Recursive identification Gradient search Parameter estimation Performance analysis
ISSN:	0924-090X, 1573-269X
Online Access:	Get full text
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