Fast Adaptive Active Noise Control Based on Modified Model-Agnostic Meta-Learning Algorithm

With the advent of efficient low-cost processors and electroacoustic components, there is renewed interest in the practical implementation of active noise control (ANC). However, the slow convergence of conventional adaptive algorithms deployed in ANC restricts its handling of typical amplitude-vary...

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Vydané v:	IEEE signal processing letters Ročník 28; s. 593 - 597
Hlavní autori:	Shi, Dongyuan, Gan, Woon-Seng, Lam, Bhan, Ooi, Kenneth
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Acceleration Active noise control Adaptation models Adaptive algorithms Adaptive control Adaptive filters Adaptive systems Amplitudes control filter initialization Convergence Cost function fast adaptation FxLMS LF noise Machine learning Mathematical models model-agnostic meta-learning Noise control Noise measurement Signal processing algorithms
ISSN:	1070-9908, 1558-2361
On-line prístup:	Získať plný text
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