Journal article
Recursive direct weight optimization in nonlinear system identification : A minimal probability approach
IEEE transactions on automatic control, Vol.52(7), pp.1218-1231
2007
DOI: 10.1109/TAC.2007.900826
Abstract
In this paper, a direct weight optimization method is proposed for nonlinear system identification based on a 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
- Recursive direct weight optimization in nonlinear system identification : A minimal probability approach
- Creators
- Er-Wei BAI - Department of Electrical and Computer Engineering, University of Iowa, Iowa City, IA 52242, United StatesYUN LIU - Department of Electrical and Computer Engineering, University of Iowa, Iowa City, IA 52242, United States
- Resource Type
- Journal article
- Publication Details
- IEEE transactions on automatic control, Vol.52(7), pp.1218-1231
- Publisher
- Institute of Electrical and Electronics Engineers
- DOI
- 10.1109/TAC.2007.900826
- ISSN
- 0018-9286
- eISSN
- 1558-2523
- Language
- English
- Date published
- 2007
- Academic Unit
- Electrical and Computer Engineering
- Record Identifier
- 9984083838302771
Metrics
12 Record Views