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A Data-Driven Orthogonal Basis Function Approach for Non-Parametric Nonlinear System Identification
System Identification, Volume # 15 | Part# 1
Location: Saint-Malo Convention Center, Saint-Malo, France
National Organizing Committee Chair: Basseville, Michele
International Program Committee Chair: Vicino, Antonio,
Panciatici, Patrick
Conference Editor: Walter, Eric
Authors
Bai, Er-Wei
Identifier
10.3182/20090706-3-FR-2004.00220
Index Terms
Nonlinear System Identification; Nonparametric Methods
Abstract
A data driven orthogonal basis function approach is proposed for non-parametric FIR nonlinear system identification. This eliminates the problem of blindly choosing the basis functions without a priori structural information. Extension to deterministic inputs are also presented. Further, based on the proposed basis functions, approaches are proposed for model order determination and regressor selection along with their theoretical justifications.
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