2001Unpublished venueRequires access

Continuous nonlinear system identification using Volterra series expansion

S. Hassouna, Patrick Coirault, Régis Ouvrard

Open publisher page 4 citations

Abstract

This paper presents an identification method for continuous nonlinear systems whose input-output functional is regular and homogeneous. The model is a Volterra series truncated in its first terms. The Volterra kernels are expanded on multidimensional generalized orthonormal bases. A subset model selection is applied on the estimated model to provide a more parsimonious model.

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What this paper is about

This paper presents an identification method for continuous nonlinear systems whose input-output functional is regular and homogeneous. The model is a Volterra series truncated in its first terms. The Volterra kernels are expanded on multidimensional generalized orthonormal bases. A subset model selection is applied on the estimated model to provide a more parsimonious model.

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OpenAlex reports 4 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

This paper presents an identification method for continuous nonlinear systems whose input-output functional is regular and homogeneous. The model is a Volterra series truncated in its first terms. The Volterra kernels are expanded on multidimensional generalized orthonormal bases. A subset model selection is applied on the estimated model to provide a more parsimonious model.

Key concepts: Volterra series, Orthonormal basis, Nonlinear system identification, Nonlinear system, Series (stratigraphy), Identification (biology), Applied mathematics, System identification

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