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Speeding up VSLMS adaptation algorithms using dynamic adaptation gain: Analysis and Applications

Year: 2024

Type: preprint

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.

Source: arXiv (Cornell University)

DOI: 10.48550/arxiv.2404.12672

Authors: Landau, Ioan Doré, Bismor, Dariusz, Airimitoaie, Tudor-Bogdan, Vau, Bernard, Buche, Gabriel

Institutions: GIPSA-Lab, Silesian University of Technology, Laboratoire de l'Intégration du Matériau au Système, Grain Inspection, Packers and Stockyards Administration, iXBlue (France)

Language: English

Topic: Advanced Adaptive Filtering Techniques

Subfield: Computational Mechanics

Field: Engineering

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W4394970287

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