Least-Squares Support Vector Machines for the identification of Wiener–Hammerstein systems-Reference-Cited by-同舟云学术

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Least-Squares Support Vector Machines for the identification of Wiener–Hammerstein systems

Published:2012-11 Issue:11 Volume:20 Page:1165-1174
ISSN:0967-0661
Container-title:Control Engineering Practice
language:en
Short-container-title:Control Engineering Practice

Author:

Falck Tillmann,Dreesen Philippe,De Brabanter Kris,Pelckmans Kristiaan,De Moor Bart,Suykens Johan A.K.

Publisher

Elsevier BV

Subject

Applied Mathematics,Electrical and Electronic Engineering,Computer Science Applications,Control and Systems Engineering

Reference39 articles.

1. An optimal two-stage identification algorithm for Hammerstein–Wiener nonlinear systems;Bai;Automatica,1998

2. Recursive direct weight optimization in nonlinear system identification: A minimal probability approach;Bai;IEEE Transactions on Automatic Control,2007

3. Analysis of stochastic gradient identification of Wiener–Hammerstein systems for nonlinearities with Hermite polynomial expansions;Bershad;IEEE Transactions on Signal Processing,2001

4. Identification of a class of nonlinear systems using correlation analysis;Billings;Proceedings of IEE,1978

5. Recursive identification method for MISO Wiener–Hammerstein model;Boutayeb;IEEE Transactions on Automatic Control,1995

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