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Communication Dans Un Congrès Année : 2007

Recursive subspace identification of Hammerstein models based on LS-SVM

Résumé

This paper presents a recursive scheme for the identification of Hammerstein MIMO models. The Markov parameters of the system are determined first by a Least Squares Support Vector Machines (LS-SVM) regression through an over-parameterization technique. Then, a state space realization of the system is retrieved using an adapted online subspace identification method. Simulation results are provided to demonstrate the effectiveness of the algorithm in the presence of white output noise.
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Dates et versions

hal-00180151 , version 1 (17-10-2007)

Identifiants

  • HAL Id : hal-00180151 , version 1

Citer

Laurent Bako, Guillaume Mercère, Stéphane Lecoeuche, Marco Lovera. Recursive subspace identification of Hammerstein models based on LS-SVM. Adaptation and Learning in Control and Signal Processing 2007, ALCOSP'07, Aug 2007, Saint Petersburg, Russia. pp.CDROM. ⟨hal-00180151⟩
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