Dynamic variable step size LMS adaptation algorithms -- Application to adaptive feedforward noise attenuation

Fuente: arXiv
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Hauptverfasser: Airimitoaie, Tudor-Bogdan, Vau, Bernard, Bismor, Dariusz, Buche, Gabriel, Landau, Ioan Doré
Format: Preprint
Veröffentlicht: 2024
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author Airimitoaie, Tudor-Bogdan
Vau, Bernard
Bismor, Dariusz
Buche, Gabriel
Landau, Ioan Doré
author_facet Airimitoaie, Tudor-Bogdan
Vau, Bernard
Bismor, Dariusz
Buche, Gabriel
Landau, Ioan Doré
contents The paper explores in detail 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. Criteria for the selection of the coefficients of the DAG filter which is required to be a strictly positive real transfer operator are given. The potential of the VS-LMS adaptation algorithms using a DAG is then illustrated by experimental results obtained on a relevant adaptive active noise attenuation system.
format Preprint
id arxiv_https___arxiv_org_abs_2403_13381
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Dynamic variable step size LMS adaptation algorithms -- Application to adaptive feedforward noise attenuation
Airimitoaie, Tudor-Bogdan
Vau, Bernard
Bismor, Dariusz
Buche, Gabriel
Landau, Ioan Doré
Optimization and Control
The paper explores in detail 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. Criteria for the selection of the coefficients of the DAG filter which is required to be a strictly positive real transfer operator are given. The potential of the VS-LMS adaptation algorithms using a DAG is then illustrated by experimental results obtained on a relevant adaptive active noise attenuation system.
title Dynamic variable step size LMS adaptation algorithms -- Application to adaptive feedforward noise attenuation
topic Optimization and Control
url https://arxiv.org/abs/2403.13381