Comments on “Fractional LMS algorithm”

The purpose of this note is to point out that the recently proposed fractional least mean squares (FLMS) algorithm, whose derivation is based on fractional derivative, is not suitable for adaptive signal processing. Our claims are verified via extensive simulation results with comparison with the le...

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Published inSignal processing Vol. 133; pp. 219 - 226
Main Authors Bershad, Neil J., Wen, Fuxi, So, Hing Cheung
Format Journal Article
LanguageEnglish
Published Elsevier B.V 01.04.2017
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ISSN0165-1684
1872-7557
DOI10.1016/j.sigpro.2016.11.009

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Abstract The purpose of this note is to point out that the recently proposed fractional least mean squares (FLMS) algorithm, whose derivation is based on fractional derivative, is not suitable for adaptive signal processing. Our claims are verified via extensive simulation results with comparison with the least mean squares (LMS) algorithm, indicating that the new method does not have any advantages over the classical one.
AbstractList The purpose of this note is to point out that the recently proposed fractional least mean squares (FLMS) algorithm, whose derivation is based on fractional derivative, is not suitable for adaptive signal processing. Our claims are verified via extensive simulation results with comparison with the least mean squares (LMS) algorithm, indicating that the new method does not have any advantages over the classical one.
Author Wen, Fuxi
So, Hing Cheung
Bershad, Neil J.
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Keywords Fractional least mean squares algorithm
Least mean squares algorithm
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Least mean squares algorithm
Title Comments on “Fractional LMS algorithm”
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