Work

Can dynamic adaptation gain speed up recursive least squares algorithm?

Year: 2024

Type: conference-paper

Abstract: Dynamic adaptation gain/learning rate have been introduced in the context of adaptation/learning algorithms using scalar adaptation gains/learning rates in order to accelerate the adaptation transients. This paper shows by means of theoretical analysis, simulations and experimental results (on an active noise control system) that inserting a dynamic adaptation gain into the recursive least squares algorithm speeds up the adaptation transients in a deterministic environment and the asymptotic convergence in the stochastic case.

Source: Proceedings of the IEEE Conference on Decision & Control, including the Symposium on Adaptive Processes

DOI: 10.1109/cdc56724.2024.10886185

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

Institutions: Institut polytechnique de Grenoble, Centre National de la Recherche Scientifique, GIPSA-Lab, Université de Bordeaux, Laboratoire de l'Intégration du Matériau au Système, Institut Polytechnique de Bordeaux, Exail (France)

Language: English

Topic: Advanced Adaptive Filtering Techniques

Subfield: Computational Mechanics

Field: Engineering

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W4404686442

FWCI:

Cites: 4

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Related to: 10