Gradient-based iterative parameter estimation for Box–Jenkins systems

This paper presents a gradient-based iterative identification algorithms for Box–Jenkins systems with finite measurement input/output data. Compared with the pseudo-linear regression stochastic gradient approach, the proposed algorithm updates the parameter estimation using all the available data at...

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Bibliographic Details
Published in:	Computers & mathematics with applications (1987) Vol. 60; no. 5; pp. 1200 - 1208
Main Authors:	Wang, Dongqing, Yang, Guowei, Ding, Ruifeng
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 01.09.2010
Subjects:	Algorithms Box–Jenkins models Computation Iterative algorithms Iterative methods Mathematical analysis Mathematical models Parameter estimation Recursive dentification Regression Signal processing Stochastic gradient Stochasticity Signal processing Parameter estimation Recursive dentification Iterative algorithms Box–Jenkins models Stochastic gradient
ISSN:	0898-1221, 1873-7668
Online Access:	Get full text
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