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ADAPTIVE NEURAL NETWORK FOR FEEDBACK ACTIVE NOISE CONTROL SYSTEM

Tuan Van Huynh 1, *
Phuong Huu Nguyen 1
Long Ngoc Nguyen 2
  1. University of Science, VNU-HCMC
  2. Ton Duc Thang University
Correspondence to: Tuan Van Huynh, University of Science, VNU-HCMC. Email: pvphuc@hcmuns.edu.vn.
Volume & Issue: Vol. 12 No. 12 (2009) | Page No.: 86-93 | DOI: 10.32508/stdj.v12i12.2323
Published: 2009-06-28

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Copyright The Author(s) 2023. This article is published with open access by Vietnam National University, Ho Chi Minh city, Vietnam. This article is distributed under the terms of the Creative Commons Attribution License (CC-BY 4.0) which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited. 

Abstract

This paper presents a neural-based filtered-X least-mean-square algorithm (NFXLMS) active noise control (ANC) system. The saturation of the power amplifier in ANC system is considered. A method for compensating the saturation is proposed. On line dynamic learning algorithms based on the error gradient descent method is carried out. The convergence of the algorithm is proven using a discrete Lyapunov function. Simulation results are provided for illustration.

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