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The Least-Squares Identification of FIR Systems Subject to Worst-Case Noise
Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
1993 (engelsk)Rapport (Annet vitenskapelig)
Abstract [en]

The least-squares identification of FIR systems is analyzed assuming that the noise is a bounded signal and the input signal is a pseudo-random binary sequence. A lower bound on the worst-case transfer function error shows that the lest-square estimate of the transfer function diverges as the order of the FIR system is increased. This implies that, in the presence of the worst-case noise, the trade-off between the estimation error due to the disturbance and the bias error (due to unmodeled dynamics) is significantly different from the corresponding trade-off in the random error case: with a worst-case formulation, the model complexity should not increase indefinitely as the size of the data set increases.

sted, utgiver, år, opplag, sider
Linköping: Linköping University , 1993. , s. 13
Serie
LiTH-ISY-R, ISSN 1400-3902 ; 1479
Emneord [en]
Worst-case identification, FIR systems, Leat-squares algorithm, Cybernetik Informationsteori, Maskinelement Servomekanismer Automation
HSV kategori
Identifikatorer
URN: urn:nbn:se:liu:diva-95854ISRN: LiTH-ISY-R-1479OAI: oai:DiVA.org:liu-95854DiVA, id: diva2:638458
Tilgjengelig fra: 2013-07-30 Laget: 2013-07-30 Sist oppdatert: 2014-06-18bibliografisk kontrollert

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