Zhao, W, Chen, H-F, Bai, E-W et al. (1 more author) (2015) Kernel-based local order estimation of nonlinear nonparametric systems. Automatica, 51. pp. 243-254. ISSN 0005-1098
Abstract
We consider the local order estimation of nonlinear autoregressive systems with exogenous inputs (NARX), which may have different local dimensions at different points. By minimizing the kernel-based local information criterion introduced in this paper, the strongly consistent estimates for the local orders of the NARX system at points of interest are obtained. The modification of the criterion and a simple procedure of searching the minimum of the criterion, are also discussed. The theoretical results derived here are tested by simulation examples.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2014 Elsevier Ltd. This is an author produced version of a paper published in Automatica. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Nonlinear ARX system; Recursive local linear estimator; Order estimation; Strong consistency |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Institute of Communication & Power Networks (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 18 Mar 2019 15:30 |
Last Modified: | 19 Mar 2019 08:40 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.automatica.2014.10.069 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:143809 |
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