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Low complexity dynamically regularised RLS algorithm

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Low complexity dynamically regularised RLS algorithm. / Liu, J.; Zakharov, Y.

In: Electronics Letters, Vol. 44, No. 14, 03.07.2008, p. 886-U219.

Research output: Contribution to journalArticle

Harvard

Liu, J & Zakharov, Y 2008, 'Low complexity dynamically regularised RLS algorithm', Electronics Letters, vol. 44, no. 14, pp. 886-U219. https://doi.org/10.1049/el:20081096

APA

Liu, J., & Zakharov, Y. (2008). Low complexity dynamically regularised RLS algorithm. Electronics Letters, 44(14), 886-U219. https://doi.org/10.1049/el:20081096

Vancouver

Liu J, Zakharov Y. Low complexity dynamically regularised RLS algorithm. Electronics Letters. 2008 Jul 3;44(14):886-U219. https://doi.org/10.1049/el:20081096

Author

Liu, J. ; Zakharov, Y. / Low complexity dynamically regularised RLS algorithm. In: Electronics Letters. 2008 ; Vol. 44, No. 14. pp. 886-U219.

Bibtex - Download

@article{8dedc75b3809447288cefd02bb75d89a,
title = "Low complexity dynamically regularised RLS algorithm",
abstract = "Proposed is a low complexity dynamically regularised recursive least squares (RLS) adaptive filtering algorithm based on dichotomous co- ordinate descent iterations. The complexity of the proposed algorithm is reduced to O(N-2), N being the filter length, compared to O(N-3) for a directly regularised RLS algorithm. Field programmable gate array implementation shows that the proposed algorithm is hardware efficient.",
author = "J. Liu and Y. Zakharov",
year = "2008",
month = "7",
day = "3",
doi = "10.1049/el:20081096",
language = "English",
volume = "44",
pages = "886--U219",
journal = "Electronics Letters",
issn = "0013-5194",
publisher = "Institution of Engineering and Technology",
number = "14",

}

RIS (suitable for import to EndNote) - Download

TY - JOUR

T1 - Low complexity dynamically regularised RLS algorithm

AU - Liu, J.

AU - Zakharov, Y.

PY - 2008/7/3

Y1 - 2008/7/3

N2 - Proposed is a low complexity dynamically regularised recursive least squares (RLS) adaptive filtering algorithm based on dichotomous co- ordinate descent iterations. The complexity of the proposed algorithm is reduced to O(N-2), N being the filter length, compared to O(N-3) for a directly regularised RLS algorithm. Field programmable gate array implementation shows that the proposed algorithm is hardware efficient.

AB - Proposed is a low complexity dynamically regularised recursive least squares (RLS) adaptive filtering algorithm based on dichotomous co- ordinate descent iterations. The complexity of the proposed algorithm is reduced to O(N-2), N being the filter length, compared to O(N-3) for a directly regularised RLS algorithm. Field programmable gate array implementation shows that the proposed algorithm is hardware efficient.

UR - http://www.scopus.com/inward/record.url?scp=46649093410&partnerID=8YFLogxK

U2 - 10.1049/el:20081096

DO - 10.1049/el:20081096

M3 - Article

VL - 44

SP - 886-U219

JO - Electronics Letters

JF - Electronics Letters

SN - 0013-5194

IS - 14

ER -