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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.
1994 (engelsk)Inngår i: Systems & control letters (Print), ISSN 0167-6911, E-ISSN 1872-7956, Vol. 23, nr 5, s. 329-338Artikkel i tidsskrift (Fagfellevurdert) Published
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 least-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
1994. Vol. 23, nr 5, s. 329-338
Emneord [en]
Worst-case identification, FIR systems, Least-squares algorithm
HSV kategori
Identifikatorer
URN: urn:nbn:se:liu:diva-56339DOI: 10.1016/0167-6911(94)90065-5OAI: oai:DiVA.org:liu-56339DiVA, id: diva2:318615
Tilgjengelig fra: 2010-05-09 Laget: 2010-05-07 Sist oppdatert: 2017-12-12

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