GPU implementation of a fast active noise control algorithm with multiple reference signals

Traditional active noise control (ANC) systems are mostly implemented on digital signal processor (DSP). Due to the inadequate computational power of the DSP, especially in applications with multiple reference signals, the DSP is unable to update the optimal control filter for different types of noise. Hence, Graphics Processing Unit (GPU) has been incorporated to the ANC system to enhance its computational power. In this work, a DSP-CPU-GPU computing architecture is adopted to improve the computational performance of the ANC system and ensure the real-time signal processing. In addition, a fast ANC algorithm on the GPU is employed to update the control filters to handle different reference signals. Finally, the effectiveness of the method is verified by experiments in the condition of multiple reference signals.

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Publication Details

Journal
NOISE-CON proceedings
Published
2024-10-04
DOI
https://doi.org/10.3397/in_2024_3204
Primary Topic
Advanced Adaptive Filtering Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

GPU implementation of a fast active noise control algorithm with multiple reference signals

Hongling Sun, J. Liu, Jun Yang, Jianguo Wen et al.
NOISE-CON proceedings
Advanced Adaptive Filtering Techniques
article

GPU implementation of a fast active noise control algorithm with multiple reference signals

Hongling Sun, J. Liu, Jun Yang, Jianguo Wen, Ming Wu, Han Wang
article en

Abstract

Traditional active noise control (ANC) systems are mostly implemented on digital signal processor (DSP). Due to the inadequate computational power of the DSP, especially in applications with multiple reference signals, the DSP is unable to update the optimal control filter for different types of noise. Hence, Graphics Processing Unit (GPU) has been incorporated to the ANC system to enhance its computational power. In this work, a DSP-CPU-GPU computing architecture is adopted to improve the computational performance of the ANC system and ensure the real-time signal processing. In addition, a fast ANC algorithm on the GPU is employed to update the control filters to handle different reference signals. Finally, the effectiveness of the method is verified by experiments in the condition of multiple reference signals.

NOISE-CON proceedingsVol. 270(9)
Chinese Academy of Sciences (CN), Institute of Acoustics (CN)
Affordable and clean energy
Openalex Percentile: Top 81%
Advanced Adaptive Filtering Techniques
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GPU implementation of a fast active noise control algorithm with multiple reference signals — Hongling Sun, J. Liu, et al. · NOISE-CON proceedings (2024) | TGRS Research Map | TGRS