Initializing Wiener-Hammerstein models based on partitioning of the best linear approximation
type: Item
instance of: scholarly article
title: Initializing Wiener-Hammerstein models based on partitioning of the best linear approximation
zbMATH Open document ID: 1260.93167
author: Yanyan Li
published in: Automatica
publication date: 2013-03-12T00:00:00Z
Mathematics Subject Classification ID: 93E12
Mathematics Subject Classification ID: 93E10
zbMATH DE Number: 6143427
zbMATH Keywords: Wiener--Hammerstein systems
zbMATH Keywords: Hammerstein systems
zbMATH Keywords: Wiener systems
zbMATH Keywords: nonlinear system identification
describes a project that uses: Mathematica
MaRDI profile type: Publication
full work available at URL: j.automatica.2011.07.007
OpenAlex ID: W1971599042
cites work: Convergence of the Iterative Hammerstein System Identification Algorithm
cites work: Identification of systems containing linear dynamic and static nonlinear elements
cites work: Recursive identification method for MISO Wiener-Hammerstein model
cites work: The identification of a particular nonlinear time series system
cites work: Linear approximations of nonlinear FIR systems for separable input processes
cites work: Nonlinear black-box models in system identification: Mathematical foundations
cites work: Convergence analysis of parametric identification methods
cites work: Frequency domain system identification with missing data
cites work: Parametric and nonparametric identification of linear systems in the presence of nonlinear distortions-a frequency domain approach
cites work: Identification of linear systems with nonlinear distortions
cites work: Initial estimates for the dynamics of a Hammerstein system
cites work: Nonlinear black-box modeling in system identification: A unified overview
cites work: On covariance function tests used in system identification
cites work: Identifying MIMO Hammerstein systems in the context of subspace model identification methods
cites work: Parameter identification of Wiener systems with multisegment piecewise-linear nonlinearities
cites work: Recusrsive prediction error identification using the nonlinear Wiener model
DOI: 10.1016/J.AUTOMATICA.2011.07.007
description: scientific article; zbMATH DE number 6143427