Mixed-Gradients Distributed Filtered Reference Least Mean Square Algorithm - A Robust Distributed Multichannel Active Noise Control Algorithm
Distributed multichannel active noise control (DMCANC), which utilizes multiple individual processors to achieve a global noise reduction performance comparable to conventional centralized multichannel active noise control (MCANC), has become increasingly attractive due to its high computational eff...
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| Vydáno v: | IEEE Transactions on Audio, Speech and Language Processing Ročník 33; s. 1563 - 1575 |
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| Jazyk: | angličtina |
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2025
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| ISSN: | 2998-4173, 2998-4173 |
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| Abstract | Distributed multichannel active noise control (DMCANC), which utilizes multiple individual processors to achieve a global noise reduction performance comparable to conventional centralized multichannel active noise control (MCANC), has become increasingly attractive due to its high computational efficiency. However, the majority of current DMCANC algorithms disregard the impact of crosstalk across nodes and impose the assumption of an ideal network devoid of communication limitations, which is an unrealistic assumption. Therefore, this work presents a robust DMCANC algorithm that employs the compensating filter to mitigate the impact of crosstalk. The proposed solution enhances the DMCANC system's flexibility and security by utilizing local gradients instead of local control filters to convey enhanced information, resulting in a mixed-gradients distributed filtered reference least mean square (MGDFxLMS) algorithm. The performance investigation demonstrates that the proposed approach performs well with the centralized method. Furthermore, to address the issue of communication delay in the distributed network, a practical strategy that auto-shrinks the step size value in response to the delayed samples is implemented to improve the system's resilience. The numerical simulation results demonstrate the efficacy of the proposed auto-shrink step size MGDFxLMS (ASSS-MGDFxLMS) algorithm across various communication delays, highlighting its practical value. |
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| AbstractList | Distributed multichannel active noise control (DMCANC), which utilizes multiple individual processors to achieve a global noise reduction performance comparable to conventional centralized multichannel active noise control (MCANC), has become increasingly attractive due to its high computational efficiency. However, the majority of current DMCANC algorithms disregard the impact of crosstalk across nodes and impose the assumption of an ideal network devoid of communication limitations, which is an unrealistic assumption. Therefore, this work presents a robust DMCANC algorithm that employs the compensating filter to mitigate the impact of crosstalk. The proposed solution enhances the DMCANC system's flexibility and security by utilizing local gradients instead of local control filters to convey enhanced information, resulting in a mixed-gradients distributed filtered reference least mean square (MGDFxLMS) algorithm. The performance investigation demonstrates that the proposed approach performs well with the centralized method. Furthermore, to address the issue of communication delay in the distributed network, a practical strategy that auto-shrinks the step size value in response to the delayed samples is implemented to improve the system's resilience. The numerical simulation results demonstrate the efficacy of the proposed auto-shrink step size MGDFxLMS (ASSS-MGDFxLMS) algorithm across various communication delays, highlighting its practical value. |
| Author | Shi, Dongyuan Gan, Woon-Seng Ji, Junwei |
| Author_xml | – sequence: 1 givenname: Junwei orcidid: 0009-0006-4609-5131 surname: Ji fullname: Ji, Junwei email: JUNWEI002@e.ntu.edu.sg organization: School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore – sequence: 2 givenname: Dongyuan orcidid: 0000-0003-0768-6386 surname: Shi fullname: Shi, Dongyuan email: dongyuan.shi@nwpu.edu.cn organization: Center of Intelligent Acoustics and Immersive Communications, Northwestern Polytechnical University, Xi'an, China – sequence: 3 givenname: Woon-Seng orcidid: 0000-0002-7143-1823 surname: Gan fullname: Gan, Woon-Seng email: ewsgan@ntu.edu.sg organization: School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore |
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| SubjectTerms | Acoustics Active Noise Control (ANC) auto -shrink step size (ASSS) communication restrictions compensation filter Crosstalk Delays distributed control Filtering algorithms Information filters mixed -gradient distributed filtered reference least mean square (MGDFxLMS) Noise Noise reduction Sensors Signal processing algorithms Training |
| Title | Mixed-Gradients Distributed Filtered Reference Least Mean Square Algorithm - A Robust Distributed Multichannel Active Noise Control Algorithm |
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