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Linear Approximations of Nonlinear FIR Systems for Separable Input Processes
Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.ORCID-id: 0000-0003-4881-8955
2005 (engelsk)Inngår i: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 41, nr 3, s. 459-473Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

Nonlinear systems can be approximated by linear time-invariant (LTI) models in-many ways. Here, LTI models that are optimal approximations in the mean-square error sense are analyzed. A necessary and sufficient condition on the input signal for the optimal LTI approximation of an arbitrary nonlinear finite impulse response (NFIR) system to be a linear finite impulse response (FIR) model is presented. This condition says that the in ut should be separable of a certain order, i.e., that certain conditional expectations should be,P linear. For the special case of Gaussian input signals, this condition is closely related to a generalized version of Bussgang's classic theorem about static nonlinearities. It is shown that this generalized theorem can be used for structure identification and for the identification of generalized Wiener-Hammerstein systems.

sted, utgiver, år, opplag, sider
Elsevier, 2005. Vol. 41, nr 3, s. 459-473
Emneord [en]
System identification, Mean-square error, Nonlinear systems, Linearization
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Identifikatorer
URN: urn:nbn:se:liu:diva-46142DOI: 10.1016/j.automatica.2004.11.016OAI: oai:DiVA.org:liu-46142DiVA, id: diva2:267038
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© 2004 Elsevier Ltd. All rights reserved.

Tilgjengelig fra: 2009-10-11 Laget: 2009-10-11 Sist oppdatert: 2024-01-08

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