Variance Aspects of L2 Model Reduction when Undermodeling - the Output Error Case
2002 (English)Report (Other academic)
In this contribution, variance properties of L2 model reduction are studied. That is, given an estimated model of high order we study the resulting variance of an L2reduced approximation. The main result of the paper is showing that estimating a low order output error (OE) model via L2 model reduction of a high order model gives a smaller variance compared to estimating a low order model directly from data in the case of undermodeling. This has previously been shown to hold for FIR (Finite Impulse Response) models, but is in this paper extended to general linear OE models.
Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2002. , 14 p.
LiTH-ISY-R, ISSN 1400-3902 ; 2405
Identification, Model reduction, Variance
IdentifiersURN: urn:nbn:se:liu:diva-55858ISRN: LiTH-ISY-R-2405OAI: oai:DiVA.org:liu-55858DiVA: diva2:316679