Speeding up VSLMS adaptation algorithms using dynamic adaptation gain: Analysis and Applications
Abstract
The paper explores the use of dynamic adaptation gain/step size (DAG) for improving the adaptation transient performance of variable step-size LMS (VS-LMS) adaptation algorithms. A generic form for the implementation of the DAG within the VS-LMS algorithms is provided. The properties of the VS-LMS algorithms using dynamic adaptation gain are discussed in detail. Stability issues in deterministic environment and convergence properties in stochastic environment are examined. A transient performance analysis is proposed. Criteria for the selection of the coefficients of the DAG filter are provided.The potential of the VS-LMS adaptation algorithms using a DAG is then illustrated by simulation results (adaptive line enhancer, filter identification) and experimental results obtained on a relevant adaptive active noise attenuation system.
Keywords
Cite
@article{arxiv.2404.12672,
title = {Speeding up VSLMS adaptation algorithms using dynamic adaptation gain: Analysis and Applications},
author = {Ioan Doré Landau and Dariusz Bismor and Tudor-Bogdan Airimitoaie and Bernard Vau and Gabriel Buche},
journal= {arXiv preprint arXiv:2404.12672},
year = {2024}
}
Comments
arXiv admin note: substantial text overlap with arXiv:2403.13381