Continuous nonlinear system identification using Volterra series expansion
S. Hassouna, Patrick Coirault, Régis Ouvrard
Abstract
S. Hassouna, Patrick Coirault, Régis Ouvrard
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.
OpenAlex reports 4 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
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