Book chapter
A Data-Driven Basis Function Approach in Nonparametric Nonlinear System Identification
Uncertainty in Complex Networked Systems, pp.349-395
Systems & Control: Foundations & Applications, Springer International Publishing
12/15/2018
DOI: 10.1007/978-3-030-04630-9_10
Abstract
In this chapter, a data-driven orthogonal basis function approach is proposed for nonparametric FIR nonlinear system identification. The basis functions are not fixed a priori and match the structure of the unknown system automatically. This eliminates the problem of blindly choosing the basis functions without a priori structural information. Further, based on the proposed basis functions, approaches are proposed for model order determination and regressor selection along with their theoretical justifications. Both random inputs and deterministic inputs are considered.
Details
- Title: Subtitle
- A Data-Driven Basis Function Approach in Nonparametric Nonlinear System Identification
- Creators
- Er-Wei Bai - University of IowaChangming Cheng - University of Iowa
- Resource Type
- Book chapter
- Publication Details
- Uncertainty in Complex Networked Systems, pp.349-395
- Publisher
- Springer International Publishing; Cham
- Series
- Systems & Control: Foundations & Applications
- DOI
- 10.1007/978-3-030-04630-9_10
- eISSN
- 2324-9757
- ISSN
- 2324-9749
- Language
- English
- Date published
- 12/15/2018
- Academic Unit
- Electrical and Computer Engineering
- Record Identifier
- 9984197550002771
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