A local information criterion for order identification of nonlinear ARX systems

Wenxiao Zhao; Han-Fu Chen; Er-Wei Bai; Kang Li

doi:10.1109/ASCC.2013.6606337

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Conference proceeding

A local information criterion for order identification of nonlinear ARX systems

Wenxiao Zhao, Han-Fu Chen, Er-Wei Bai and Kang Li

2013 9th Asian Control Conference (ASCC), pp.1-6

06/2013

DOI: 10.1109/ASCC.2013.6606337

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Abstract

We consider the local order estimation of non-parametric nonlinear autoregressive systems with exogenous inputs (NARX), which may have different local dimensions at different points of interest. By minimizing the kernel-based local information criterion introduced in the paper, the strongly consistent estimates for the local orders of the NARX system at of interest points are obtained. The theoretical result derived here is tested by a simulation example.

Noise

Convergence

Estimation

Kernel

Nonlinear ARX system

Nonlinear systems

order estimation

Probability density function

recursive local linear estimator

strong consistency

Upper bound

Details

Title: Subtitle: A local information criterion for order identification of nonlinear ARX systems
Creators: Wenxiao Zhao - Key Lab. of Syst. & Control, Acad. of Math. & Syst. Sci., Beijing, China
Han-Fu Chen - Key Lab. of Syst. & Control, Acad. of Math. & Syst. Sci., Beijing, China
Er-Wei Bai - University of Iowa
Kang Li - Queen's University Belfast
Resource Type: Conference proceeding
Publication Details: 2013 9th Asian Control Conference (ASCC), pp.1-6
DOI: 10.1109/ASCC.2013.6606337
Publisher: IEEE
Language: English
Date published: 06/2013
Academic Unit: Electrical and Computer Engineering
Record Identifier: 9984197334302771

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