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On the Choice of Norms in System Identification
Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
1994 (engelsk)Rapport (Annet vitenskapelig)
Abstract [en]

In this paper we discuss smooth and sensitive norms for prediction error system identification when the disturbances are magnitude bounded. Formal conditions for sensitive norms, which give an order of magnitude faster convergence of the parameter estimate variance, are developed. However, it also is shown that the parameter estimate variance convergence rate of sensitive norms is arbitrarily bad for certain distributions. A necessary condition for a norm to be statistically robust with respect to the family F(C) of distributions with support [-C, C] for some arbitrary C>0 is that its second derivative does not vanish on the support. A direct consequence of this observation is that the quadratic norm is statistically robust among all lp-norms, p⩽2<∞ for F(C).

sted, utgiver, år, opplag, sider
Linköping: Linköping University , 1994. , s. 18
Serie
LiTH-ISY-R, ISSN 1400-3902 ; 1560
Emneord [en]
System identification, Sensitive norms, Bounded disturbances, Robust identification
Emneord [sv]
Cybernetik Informationsteori, Matematisk Statistik
HSV kategori
Identifikatorer
URN: urn:nbn:se:liu:diva-55157ISRN: LITH-ISY-R-1560OAI: oai:DiVA.org:liu-55157DiVA, id: diva2:315754
Tilgjengelig fra: 2010-04-29 Laget: 2010-04-29 Sist oppdatert: 2014-08-06bibliografisk kontrollert

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