Zhao, W, Chen, H-F, Bai, E-W et al. (1 more author) (2018) Local variable selection of nonlinear nonparametric systems by first order expansion. Systems & Control Letters, 111. pp. 1-8. ISSN 0167-6911
Abstract
Local variable selection by first order expansion for nonlinear nonparametric systems is investigated in the paper. By substantially modifying the algorithms developed in our earlier work (Bai et al., 2014), the previous results have been considerably strengthened under much less restrictive conditions. Firstly, the estimates generated by the modified algorithms are shown to have both the set and parameter convergence with probability one, rather than only the set convergence in probability given in our earlier work. Secondly, several technical assumptions, e.g., the lower and upper bounds on the growth of some random sequences, which practically are uncheckable, have been removed. Thirdly, not only the consistency but also the convergence rate of estimates have been established. Besides, a generalization of the proposed algorithms is also introduced.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Keywords: | Nonlinear ARX system; Variable selection; Local linear estimator; 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: | 26 Nov 2018 11:48 |
Last Modified: | 26 Nov 2018 11:48 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.sysconle.2017.10.001 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:139075 |