A frequency-domain output-constrained active noise control algorithm based on an intuitive circulant convolutional penalty factor

Due to their computational efficiency, least mean square (LMS)-based algorithms are still widely utilized to achieve optimal control in active noise control (ANC) applications. Real-world implementation of advanced ANC functionalities, such as selective cancellation of frequencies, is nonetheless ha...

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Main Authors: Shi, Dongyuan, Gan, Woon-Seng, Lam, Bhan, Shen, Xiaoyi
Other Authors: School of Electrical and Electronic Engineering
Format: Article
Language:English
Published: 2023
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Online Access:https://hdl.handle.net/10356/170255
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1702552023-09-05T02:04:56Z A frequency-domain output-constrained active noise control algorithm based on an intuitive circulant convolutional penalty factor Shi, Dongyuan Gan, Woon-Seng Lam, Bhan Shen, Xiaoyi School of Electrical and Electronic Engineering Engineering::Electrical and electronic engineering Frequency-Domain Constraint Circulant Convolution Due to their computational efficiency, least mean square (LMS)-based algorithms are still widely utilized to achieve optimal control in active noise control (ANC) applications. Real-world implementation of advanced ANC functionalities, such as selective cancellation of frequencies, is nonetheless hampered by complexity trade-offs, especially with computationally-expensive frequency-domain approaches. Prevailing time-domain adaptive algorithms - proposed to alleviate complexities from transformation - continue to incur increased complexities while constraining the magnitude of frequency bins in the time-domain filters. To address existing complexities in time-domain approaches, this paper proposes a circulant convolutional penalty factor that assists the extended leaky filtered-reference LMS (FxLMS) algorithm in achieving frequency constraint without any frequency-domain transform. This circulant convolutional penalty factor is readily determined by methods for designing finite response filters, such as frequency sampling. Additionally, the coordinate descent method is adopted to further reduce the proposed algorithm's computations, significantly increasing its feasibility for implementation on conventional real-time processors. Finally, the numerical simulations performed on the measured primary and secondary paths demonstrate the effectiveness of the proposed algorithm. Ministry of National Development (MND) National Research Foundation (NRF) This work was supported by the National Research Foundation and Ministry of National Development, Singapore, through the Cities of Tomorrow R&D Program under Grant COT-V4-2019-1. 2023-09-05T02:04:55Z 2023-09-05T02:04:55Z 2023 Journal Article Shi, D., Gan, W., Lam, B. & Shen, X. (2023). A frequency-domain output-constrained active noise control algorithm based on an intuitive circulant convolutional penalty factor. IEEE/ACM Transactions On Audio Speech and Language Processing, 31, 1318-1332. https://dx.doi.org/10.1109/TASLP.2023.3260702 2329-9290 https://hdl.handle.net/10356/170255 10.1109/TASLP.2023.3260702 2-s2.0-85153312401 31 1318 1332 en COT-V4-2019-1 IEEE/ACM Transactions on Audio Speech and Language Processing © 2023 IEEE. All rights reserved.
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Electrical and electronic engineering
Frequency-Domain Constraint
Circulant Convolution
spellingShingle Engineering::Electrical and electronic engineering
Frequency-Domain Constraint
Circulant Convolution
Shi, Dongyuan
Gan, Woon-Seng
Lam, Bhan
Shen, Xiaoyi
A frequency-domain output-constrained active noise control algorithm based on an intuitive circulant convolutional penalty factor
description Due to their computational efficiency, least mean square (LMS)-based algorithms are still widely utilized to achieve optimal control in active noise control (ANC) applications. Real-world implementation of advanced ANC functionalities, such as selective cancellation of frequencies, is nonetheless hampered by complexity trade-offs, especially with computationally-expensive frequency-domain approaches. Prevailing time-domain adaptive algorithms - proposed to alleviate complexities from transformation - continue to incur increased complexities while constraining the magnitude of frequency bins in the time-domain filters. To address existing complexities in time-domain approaches, this paper proposes a circulant convolutional penalty factor that assists the extended leaky filtered-reference LMS (FxLMS) algorithm in achieving frequency constraint without any frequency-domain transform. This circulant convolutional penalty factor is readily determined by methods for designing finite response filters, such as frequency sampling. Additionally, the coordinate descent method is adopted to further reduce the proposed algorithm's computations, significantly increasing its feasibility for implementation on conventional real-time processors. Finally, the numerical simulations performed on the measured primary and secondary paths demonstrate the effectiveness of the proposed algorithm.
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Shi, Dongyuan
Gan, Woon-Seng
Lam, Bhan
Shen, Xiaoyi
format Article
author Shi, Dongyuan
Gan, Woon-Seng
Lam, Bhan
Shen, Xiaoyi
author_sort Shi, Dongyuan
title A frequency-domain output-constrained active noise control algorithm based on an intuitive circulant convolutional penalty factor
title_short A frequency-domain output-constrained active noise control algorithm based on an intuitive circulant convolutional penalty factor
title_full A frequency-domain output-constrained active noise control algorithm based on an intuitive circulant convolutional penalty factor
title_fullStr A frequency-domain output-constrained active noise control algorithm based on an intuitive circulant convolutional penalty factor
title_full_unstemmed A frequency-domain output-constrained active noise control algorithm based on an intuitive circulant convolutional penalty factor
title_sort frequency-domain output-constrained active noise control algorithm based on an intuitive circulant convolutional penalty factor
publishDate 2023
url https://hdl.handle.net/10356/170255
_version_ 1779156769834008576