Journal article
Ranking Variables in Nonlinear Nonparametric Additive System Identification
IFAC-PapersOnLine, Vol.51(15), pp.628-633
2018
DOI: 10.1016/j.ifacol.2018.09.225
Abstract
Identification of a high dimensional nonlinear nonparametric system is costly. On the other hand for many real-world problems, they are sparse in the sense that not all variables contribute or contribute significantly. If these variables that do not contribute or contribute little can be identified and removed prior to system identification, the identification problem is of lower dimension. In this paper, depending on the identification purposes, importance measures are defined. Based on these measures, ways to calculate these measures and to rank the importance of variables are proposed. This paper addresses such questions.
Details
- Title: Subtitle
- Ranking Variables in Nonlinear Nonparametric Additive System Identification
- Creators
- Changming Cheng - University of IowaEr-wei Bai
- Resource Type
- Journal article
- Publication Details
- IFAC-PapersOnLine, Vol.51(15), pp.628-633
- DOI
- 10.1016/j.ifacol.2018.09.225
- ISSN
- 2405-8963
- eISSN
- 2405-8963
- Language
- English
- Date published
- 2018
- Academic Unit
- Electrical and Computer Engineering
- Record Identifier
- 9984197203502771
Metrics
17 Record Views