Comments on "Momentum fractional LMS for power signal parameter estimation"
Optimization and Control
2018-05-22 v1 Systems and Control
Machine Learning
Abstract
The purpose of this paper is to indicate that the recently proposed Momentum fractional least mean squares (mFLMS) algorithm has some serious flaws in its design and analysis. Our apprehensions are based on the evidence we found in the derivation and analysis in the paper titled: \textquotedblleft \textit{Momentum fractional LMS for power signal parameter estimation}\textquotedblright. In addition to the theoretical bases our claims are also verified through extensive simulation results. The experiments clearly show that the new method does not have any advantage over the classical least mean square (LMS) method.
Keywords
Cite
@article{arxiv.1805.07640,
title = {Comments on "Momentum fractional LMS for power signal parameter estimation"},
author = {Shujaat Khan and Imran Naseem and Alishba Sadiq and Jawwad Ahmad and Muhammad Moinuddin},
journal= {arXiv preprint arXiv:1805.07640},
year = {2018}
}
Comments
Least mean squares algorithm, Fractional least mean squares algorithm, Momentum fractional least mean square algorithm