\(L_{2}\) model reduction and variance reduction
type: Item
instance of: scholarly article
title: \(L_{2}\) model reduction and variance reduction
zbMATH Open document ID: 1008.93016
DOI: 10.1016/S0005-1098(02)00066-3
author: Lennart Ljung
author: Fredrik Tjärnström
published in: Automatica
publication date: 2002-09-05T00:00:00Z
review text: The authors study several variance properties related to model reduction for finite impulse response (FIR) and output error (OE) models. The variances of two models, one deduced directly from data and the other by reducing a high order model by \(L_2\) model reduction, are compared. It is shown that for the FIR case it is always better not to estimate the model from data but to use \(L_2\) model reduction of a higher order FIR model while for the OE, if the reduced model class contains the true system, the reduced model has the same variance as the directly estimated one.
Mathematics Subject Classification ID: 93B11
Mathematics Subject Classification ID: 93B30
zbMATH DE Number: 1797133
zbMATH Keywords: output error models
zbMATH Keywords: model reduction
zbMATH Keywords: identification
zbMATH Keywords: variance reduction
zbMATH Keywords: finite impulse response
Wikidata QID: Q59591957
reviewed by: Liviu Goraş
MaRDI profile type: Publication
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full work available at URL: s0005-1098(02)00066-3
OpenAlex ID: W2092183999
DBLP publication ID: journals/automatica/TjarnstromL02
description: scientific article; zbMATH DE number 1797133