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On the stability and convergence of a sliding-window variable-regularization recursive-least-squares algorithm
Univ Michigan, Dept Aerosp Engn, Ann Arbor, MI 48109 USA..
Univ Kentucky, Dept Mech Engn, 151 Ralph G Anderson Bldg, Lexington, KY 40507 USA..
Karlstads universitet, Fakulteten för hälsa, natur- och teknikvetenskap (from 2013), Institutionen för ingenjörsvetenskap och fysik. (Matematisk modellering)
Univ Michigan, Dept Aerosp Engn, Ann Arbor, MI 48109 USA..
2016 (engelsk)Inngår i: International journal of adaptive control and signal processing (Print), ISSN 0890-6327, E-ISSN 1099-1115, Vol. 30, nr 5, s. 715-735Artikkel i tidsskrift (Fagfellevurdert) Published
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Abstract [en]

A sliding-window variable-regularization recursive-least-squares algorithm is derived, and its convergence properties, computational complexity, and numerical stability are analyzed. The algorithm operates on a finite data window and allows for time-varying regularization in the weighting and the difference between estimates. Numerical examples are provided to compare the performance of this technique with the least mean squares and affine projection algorithms. Copyright (c) 2015 John Wiley & Sons, Ltd.

sted, utgiver, år, opplag, sider
John Wiley & Sons, 2016. Vol. 30, nr 5, s. 715-735
Emneord [en]
variable regularization, sliding-window RLS, digital signal processing
HSV kategori
Forskningsprogram
Elektroteknik
Identifikatorer
URN: urn:nbn:se:kau:diva-42027DOI: 10.1002/acs.2634ISI: 000373943300003OAI: oai:DiVA.org:kau-42027DiVA, id: diva2:927962
Tilgjengelig fra: 2016-05-13 Laget: 2016-05-13 Sist oppdatert: 2017-11-30bibliografisk kontrollert

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