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Non-Parametric Nonlinear System Identification: A Data-Driven Orthogonal Basis Function Approach

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1 Author(s)
Bai, E.-W. ; Dept. of Electr. & Comput. Eng., Univ. of Iowa, Iowa City, IA

In this paper, a data driven orthogonal basis function approach is proposed for non-parametric 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.

Published in:

Automatic Control, IEEE Transactions on  (Volume:53 ,  Issue: 11 )