On the stability and convergence of a sliding-window variable-regularization recursive-least-squares algorithm
2016 (English)In: International journal of adaptive control and signal processing (Print), ISSN 0890-6327, E-ISSN 1099-1115, Vol. 30, no 5, 715-735 p.Article in journal (Refereed) PublishedText
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.
Place, publisher, year, edition, pages
John Wiley & Sons, 2016. Vol. 30, no 5, 715-735 p.
variable regularization, sliding-window RLS, digital signal processing
Electrical Engineering, Electronic Engineering, Information Engineering
Research subject Electrical Engineering
IdentifiersURN: urn:nbn:se:kau:diva-42027DOI: 10.1002/acs.2634ISI: 000373943300003OAI: oai:DiVA.org:kau-42027DiVA: diva2:927962