A Computationally Efficient Leaky and Regularized RLS Filter for Its Short Length

Eisuke HORITA

doi:10.1587/transfun.E100.A.3045

A Computationally Efficient Leaky and Regularized RLS Filter for Its Short Length

Eisuke HORITA

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A Tikhonov regularized RLS algorithm with an exponential weighting factor, i.e., a leaky RLS (LRLS) algorithm was proposed by the author. A quadratic version of the LRLS algorithm also exists in the literature of adaptive filters. In this letter, a cubic version of the LRLS filter which is computationally efficient is proposed when the length of the adaptive filter is short. The proposed LRLS filter includes only a divide per iteration although its multiplications and additions increase in number. Simulation results show that the proposed LRLS filter is faster for its short length than the existing quadratic version of the LRLS filter.

Publication: IEICE TRANSACTIONS on Fundamentals Vol.E100-A No.12 pp.3045-3048

Publication Date: 2017/12/01

Publicized

Online ISSN: 1745-1337

DOI: 10.1587/transfun.E100.A.3045

Type of Manuscript: LETTER

Category: Digital Signal Processing

Authors

Eisuke HORITA
Kanazawa University

Keyword

adaptive filter, RLS, computational complexity, regularization, Tikhonov

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Eisuke HORITA, "A Computationally Efficient Leaky and Regularized RLS Filter for Its Short Length" in IEICE TRANSACTIONS on Fundamentals, vol. E100-A, no. 12, pp. 3045-3048, December 2017, doi: 10.1587/transfun.E100.A.3045.
Abstract: A Tikhonov regularized RLS algorithm with an exponential weighting factor, i.e., a leaky RLS (LRLS) algorithm was proposed by the author. A quadratic version of the LRLS algorithm also exists in the literature of adaptive filters. In this letter, a cubic version of the LRLS filter which is computationally efficient is proposed when the length of the adaptive filter is short. The proposed LRLS filter includes only a divide per iteration although its multiplications and additions increase in number. Simulation results show that the proposed LRLS filter is faster for its short length than the existing quadratic version of the LRLS filter.
URL: https://globals.ieice.org/en_transactions/fundamentals/10.1587/transfun.E100.A.3045/_p

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@ARTICLE{e100-a_12_3045,
author={Eisuke HORITA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={A Computationally Efficient Leaky and Regularized RLS Filter for Its Short Length},
year={2017},
volume={E100-A},
number={12},
pages={3045-3048},
abstract={A Tikhonov regularized RLS algorithm with an exponential weighting factor, i.e., a leaky RLS (LRLS) algorithm was proposed by the author. A quadratic version of the LRLS algorithm also exists in the literature of adaptive filters. In this letter, a cubic version of the LRLS filter which is computationally efficient is proposed when the length of the adaptive filter is short. The proposed LRLS filter includes only a divide per iteration although its multiplications and additions increase in number. Simulation results show that the proposed LRLS filter is faster for its short length than the existing quadratic version of the LRLS filter.},
keywords={},
doi={10.1587/transfun.E100.A.3045},
ISSN={1745-1337},
month={December},}

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TY - JOUR
TI - A Computationally Efficient Leaky and Regularized RLS Filter for Its Short Length
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 3045
EP - 3048
AU - Eisuke HORITA
PY - 2017
DO - 10.1587/transfun.E100.A.3045
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E100-A
IS - 12
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - December 2017
AB - A Tikhonov regularized RLS algorithm with an exponential weighting factor, i.e., a leaky RLS (LRLS) algorithm was proposed by the author. A quadratic version of the LRLS algorithm also exists in the literature of adaptive filters. In this letter, a cubic version of the LRLS filter which is computationally efficient is proposed when the length of the adaptive filter is short. The proposed LRLS filter includes only a divide per iteration although its multiplications and additions increase in number. Simulation results show that the proposed LRLS filter is faster for its short length than the existing quadratic version of the LRLS filter.
ER -