Tensor-based methods for Wiener-Hammerstein system identification

Abstract : In this paper, we propose tensor-based methods for identifying nonlinear Wiener-Hammerstein (W-H) systems. In a first step, the parameters of the linear subsystems are estimated using two different approaches based on the PARAFAC decomposition of the fifth-order Volterra kernel associated with the W-H system to be identified. The first approach consists in applying the iterative ALS algorithm, while the second approach uses the TOMFAC algorithm. In a second step, the coefficients of the nonlinear subsystem modeled as a polynomial, are estimated by means of the RLS algorithm. The proposed identification methods are illustrated by means of simulation results.
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Communication dans un congrès
10th International Multi-Conference on Systems, Signals & Devices (SSD), Mar 2013, Hammamet, Tunisia
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https://hal.archives-ouvertes.fr/hal-01246209
Contributeur : Gérard Favier <>
Soumis le : vendredi 18 décembre 2015 - 11:33:53
Dernière modification le : samedi 19 décembre 2015 - 01:05:12

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  • HAL Id : hal-01246209, version 1

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Zouhour Ben Ahmed, Nabil Derbel, Gérard Favier. Tensor-based methods for Wiener-Hammerstein system identification . 10th International Multi-Conference on Systems, Signals & Devices (SSD), Mar 2013, Hammamet, Tunisia. <hal-01246209>

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