Conference proceeding
A Minimal Probability Approach in Nonparametric Nonlinear System Identification
Proceedings of the 45th IEEE Conference on Decision and Control, pp.2500-2505
12/2006
DOI: 10.1109/CDC.2006.377114
Abstract
In this paper, a direct weight optimization method is proposed for nonlinear system identification based on the minimal probability idea. The approach has several quite attractive features and is very different from existing ones. It is optimal for any given number of finite data points and at the same time possesses asymptotic convergence. The estimator admits a closed form and no numerical optimization is needed. Theoretical analysis and numerical simulations show that the approach is a very competitive alternative to existing nonlinear identification methods
Details
- Title: Subtitle
- A Minimal Probability Approach in Nonparametric Nonlinear System Identification
- Creators
- Er-Wei Bai - Fac. of Electr. & Comput. Eng., Iowa Univ., IAYun Liu - Servo Tech Inc., Chicago, IL 60608 USA. liu_yun@servotechinc.edu
- Resource Type
- Conference proceeding
- Publication Details
- Proceedings of the 45th IEEE Conference on Decision and Control, pp.2500-2505
- Publisher
- IEEE
- DOI
- 10.1109/CDC.2006.377114
- ISSN
- 0191-2216
- Language
- English
- Date published
- 12/2006
- Academic Unit
- Electrical and Computer Engineering
- Record Identifier
- 9984197166602771
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