Comments on "Momentum fractional LMS for power signal parameter estimation"

05/19/2018
by   Shujaat Khan, et al.
0

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: “Momentum fractional LMS for power signal parameter estimation”. 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.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
02/03/2018

Parameter estimation for the mean reversion parameter for the mixed Ornstein-Uhlenbeck process

This paper constructs the skorohod integral and symmetric path-wise inte...
research
05/22/2018

A Parameter Estimation of Fractional Order Grey Model Based on Adaptive Dynamic Cat Swarm Algorithm

In this paper, we utilize ADCSO (Adaptive Dynamic Cat Swarm Optimization...
research
05/22/2018

A Parameter Estimation of Fractional Order Gray Model Based on Adaptive Dynamic Cat Swarm Algorithm

In this paper, we utilize ADCSO (Adaptive Dynamic Cat Swarm Optimization...
research
07/03/2020

Least Squares Estimator for Vasicek Model Driven by Sub-fractional Brownian Processes from Discrete Observations

We study the parameter estimation problem of Vasicek Model driven by sub...
research
10/11/2021

Performance Analysis of Fractional Learning Algorithms

Fractional learning algorithms are trending in signal processing and ada...
research
05/19/2022

Asymptotic accuracy in estimation of a fractional signal in a small white noise

This paper revisits the problem of estimating the fractional Ornstein - ...
research
07/16/2022

Signed Cumulative Distribution Transform for Parameter Estimation of 1-D Signals

We describe a method for signal parameter estimation using the signed cu...

Please sign up or login with your details

Forgot password? Click here to reset