The identification of nonlinear biological systems: Wiener and Hammerstein Cascade models
type: Item
instance of: scholarly article
title: The identification of nonlinear biological systems: Wiener and Hammerstein Cascade models
zbMATH Open document ID: 0611.92002
author: I. W. Hunter
author: M. J. Korenberg
published in: Biological Cybernetics
publication date: 1986-01-01T00:00:00Z
review text: The paper is a sequel to the preceding paper by the authors reviewed above, Zbl 0611.92001, on identification of LNL systems. Special models of these systems, namely the Hammerstein cascade model (dynamic linear subsystem preceded by a static nonlinearity) and the Wiener cascade model (dynamic linear subsystem followed by a static nonlinearity) are considered. Various identification schemes that have been proposed for these special models are critically reviewed with reference to special models arising in the identification of nonlinear biological systems. A number of deficiencies in theoretical cascade analysis is pointed out and some errors are corrected. Practical identification schemes, each of which uses a relatively short duration input, are demonstrated by numerical examples.
Mathematics Subject Classification ID: 92B05
Mathematics Subject Classification ID: 93E12
Mathematics Subject Classification ID: 93A99
Mathematics Subject Classification ID: 92F05
Mathematics Subject Classification ID: 93B30
zbMATH DE Number: 3989142
zbMATH Keywords: limited duration input-output data
zbMATH Keywords: iterative identification scheme
zbMATH Keywords: LNL systems
zbMATH Keywords: Hammerstein cascade model
zbMATH Keywords: dynamic linear subsystem
zbMATH Keywords: static nonlinearity
zbMATH Keywords: Wiener cascade model
zbMATH Keywords: nonlinear biological systems
zbMATH Keywords: Practical identification schemes
zbMATH Keywords: numerical examples
MaRDI profile type: Publication
description: scientific article; zbMATH DE number 3989142