Kernel-based local order estimation of nonlinear nonparametric systems

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

Research output: Contribution to journalArticlepeer-review

23 Citations (Scopus)
207 Downloads (Pure)

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.
Original languageEnglish
Pages (from-to)243-254
Number of pages12
JournalAutomatica
Volume51
Early online date11 Nov 2014
DOIs
Publication statusPublished - Jan 2015

Keywords

  • Nonlinear ARX system
  • Order estimation
  • Recursive local linear estimator
  • Strong consistency

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

Fingerprint Dive into the research topics of 'Kernel-based local order estimation of nonlinear nonparametric systems'. Together they form a unique fingerprint.

Cite this