Conference proceeding
Strong Consistency of Variable Selection for Stationary Linear Stochastic Systems
2019 Chinese Control Conference (CCC), Vol.2019-, pp.1719-1723
07/2019
DOI: 10.23919/ChiCC.2019.8866312
Abstract
In this paper, we consider the variable selection for linear stochastic systems. A modified LASSO-type estimator is introduced. Then based on the classical persistent excitation (PE) for systems identification, the strong consistency of the estimates is established, i.e., the zero elements in the unknown parameter vector being correctly identified and estimates for the nonzero elements in the unknown parameter vector converging to the true values with probability one. Compared with the existing results on similar topics, the strong consistency of estimates is established while in existing literature only the convergence in probability was obtained. For this, new theoretical analysis method is adopted in this paper.
Details
- Title: Subtitle
- Strong Consistency of Variable Selection for Stationary Linear Stochastic Systems
- Creators
- Wenxiao Zhao - Chinese Academy of SciencesG George Yin - Wayne State UniversityEr-Wei Bai - University of Iowa
- Resource Type
- Conference proceeding
- Publication Details
- 2019 Chinese Control Conference (CCC), Vol.2019-, pp.1719-1723
- Publisher
- Technical Committee on Control Theory, Chinese Association of Automation
- DOI
- 10.23919/ChiCC.2019.8866312
- ISSN
- 1934-1768
- eISSN
- 2161-2927
- Language
- English
- Date published
- 07/2019
- Academic Unit
- Electrical and Computer Engineering
- Record Identifier
- 9984197068002771
Metrics
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