Spatial-frequency-based selective fixed-filter algorithm for multichannel active noise control
The multichannel active noise control (MCANC) approach is widely regarded as an effective solution to achieve a large noise cancellation zone in a complicated acoustic environment. However, the sluggish convergence and massive computation of traditional adaptive multichannel active control algorithm...
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sg-ntu-dr.10356-1810322024-11-12T01:02:54Z Spatial-frequency-based selective fixed-filter algorithm for multichannel active noise control Su, Xiruo Shi, Dongyuan Zhu, Zhijuan Gan, Woon-Seng Ye, Lingyun School of Electrical and Electronic Engineering Engineering Passive localization Selective fixed-filter The multichannel active noise control (MCANC) approach is widely regarded as an effective solution to achieve a large noise cancellation zone in a complicated acoustic environment. However, the sluggish convergence and massive computation of traditional adaptive multichannel active control algorithms typically impede the MCANC system's practical applications. The recently developed selective fixed-filter method offers a way to decrease the computational load in real-time scenarios and enhance the reaction time. Nevertheless, this method is specifically designed for the single-channel ANC system and only considers the frequency information of the noise. This inevitably impacts the effectiveness of reducing noise from various directions, particularly in the MCANC system. Therefore, we proposed a spatial-frequency-based selective fixed-filter ANC technique that adopts the Bhattacharyya Distance Matching (SFANC-BdM). In our work, the BdM is a one-step spectra and is designed by calculating similarity of different data distribution. According to the most similar case, the corresponding control filter is then selected. By avoiding separately extracting the direction and frequency information, the proposed method significantly increases the algorithm's efficiency. Compared to the conventional SFANC method, it enables a more accurate filter choice and achieves better noise reduction. This work was supported by the Program of China Scholarship Council under Grant 202306320470. 2024-11-12T01:02:54Z 2024-11-12T01:02:54Z 2024 Journal Article Su, X., Shi, D., Zhu, Z., Gan, W. & Ye, L. (2024). Spatial-frequency-based selective fixed-filter algorithm for multichannel active noise control. IEEE Signal Processing Letters, 31, 2635-2639. https://dx.doi.org/10.1109/LSP.2024.3465889 1070-9908 https://hdl.handle.net/10356/181032 10.1109/LSP.2024.3465889 2-s2.0-85204908036 31 2635 2639 en IEEE Signal Processing Letters © 2024 IEEE. All rights reserved. |
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Engineering Passive localization Selective fixed-filter Su, Xiruo Shi, Dongyuan Zhu, Zhijuan Gan, Woon-Seng Ye, Lingyun Spatial-frequency-based selective fixed-filter algorithm for multichannel active noise control |
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The multichannel active noise control (MCANC) approach is widely regarded as an effective solution to achieve a large noise cancellation zone in a complicated acoustic environment. However, the sluggish convergence and massive computation of traditional adaptive multichannel active control algorithms typically impede the MCANC system's practical applications. The recently developed selective fixed-filter method offers a way to decrease the computational load in real-time scenarios and enhance the reaction time. Nevertheless, this method is specifically designed for the single-channel ANC system and only considers the frequency information of the noise. This inevitably impacts the effectiveness of reducing noise from various directions, particularly in the MCANC system. Therefore, we proposed a spatial-frequency-based selective fixed-filter ANC technique that adopts the Bhattacharyya Distance Matching (SFANC-BdM). In our work, the BdM is a one-step spectra and is designed by calculating similarity of different data distribution. According to the most similar case, the corresponding control filter is then selected. By avoiding separately extracting the direction and frequency information, the proposed method significantly increases the algorithm's efficiency. Compared to the conventional SFANC method, it enables a more accurate filter choice and achieves better noise reduction. |
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School of Electrical and Electronic Engineering |
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School of Electrical and Electronic Engineering Su, Xiruo Shi, Dongyuan Zhu, Zhijuan Gan, Woon-Seng Ye, Lingyun |
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Article |
author |
Su, Xiruo Shi, Dongyuan Zhu, Zhijuan Gan, Woon-Seng Ye, Lingyun |
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Su, Xiruo |
title |
Spatial-frequency-based selective fixed-filter algorithm for multichannel active noise control |
title_short |
Spatial-frequency-based selective fixed-filter algorithm for multichannel active noise control |
title_full |
Spatial-frequency-based selective fixed-filter algorithm for multichannel active noise control |
title_fullStr |
Spatial-frequency-based selective fixed-filter algorithm for multichannel active noise control |
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Spatial-frequency-based selective fixed-filter algorithm for multichannel active noise control |
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spatial-frequency-based selective fixed-filter algorithm for multichannel active noise control |
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2024 |
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https://hdl.handle.net/10356/181032 |
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1816858928930095104 |