# RVP-FLMS : A Robust Variable Power Fractional LMS Algorithm

## TL;DR

This paper introduces RVP-FLMS, an adaptive fractional LMS algorithm that dynamically adjusts fractional power to improve convergence speed and reduce steady-state error in system identification and channel equalization tasks.

## Contribution

The paper presents a novel adaptive framework for variable fractional power in FLMS, enhancing convergence and accuracy over existing methods.

## Key findings

- Faster convergence rate compared to FLMS
- Lower steady-state error achieved
- Effective in system identification and channel equalization

## Abstract

In this paper, we propose an adaptive framework for the variable power of the fractional least mean square (FLMS) algorithm. The proposed algorithm named as robust variable power FLMS (RVP-FLMS) dynamically adapts the fractional power of the FLMS to achieve high convergence rate with low steady state error. For the evaluation purpose, the problems of system identification and channel equalization are considered. The experiments clearly show that the proposed approach achieves better convergence rate and lower steady-state error compared to the FLMS. The MATLAB code for the related simulation is available online at https://goo.gl/dGTGmP.