Multichannel two-gradient direction filtered reference least mean square algorithm for output-constrained multichannel active noise control
Multichannel active noise control is a proven and long-standing technique for achieving a large zone of quiet in enclosures and open spaces. In practice, the multichannel active noise control system encounters more significant output saturation nonlinearity than the single-channel system as a result...
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sg-ntu-dr.10356-1721942023-11-29T01:54:31Z Multichannel two-gradient direction filtered reference least mean square algorithm for output-constrained multichannel active noise control Shi, Dongyuan Lam, Bhan Shen, Xiaoyi Gan, Woon-Seng School of Electrical and Electronic Engineering Engineering::Electrical and electronic engineering Multichannel Active Noise Control Filtered Reference Least Mean Square Multichannel active noise control is a proven and long-standing technique for achieving a large zone of quiet in enclosures and open spaces. In practice, the multichannel active noise control system encounters more significant output saturation nonlinearity than the single-channel system as a result of the increased number of multiple output amplifiers, which not only degrades noise reduction performance but also compromises system stability. Conventional output-saturation solutions are mainly designed for single-channel applications, and their high computational complexity prevents them from being extended to multichannel systems. Hence, this paper proposes a novel two-gradient direction multichannel filtered reference least mean square (FxLMS) method that effectively avoids the saturation problem by restricting the output to the desired range and marginally increasing the computation over the conventional Multichannel FxLMS algorithm. In addition, this paper investigates the step sizes of the algorithm and proposes a computation-efficient variable step-size strategy to reduce further the steady-state error caused by the varying gradient directions. Finally, the efficacy of the proposed algorithm is demonstrated through numerical simulations using measured primary and secondary paths. Ministry of National Development (MND) National Research Foundation (NRF) This research/work is supported by the Singapore Ministry of National Development and National Research Foundation under the Cities of Tomorrow R&D Program: COT-V4-2019-1. 2023-11-29T01:54:30Z 2023-11-29T01:54:30Z 2023 Journal Article Shi, D., Lam, B., Shen, X. & Gan, W. (2023). Multichannel two-gradient direction filtered reference least mean square algorithm for output-constrained multichannel active noise control. Signal Processing, 207, 108938-. https://dx.doi.org/10.1016/j.sigpro.2023.108938 0165-1684 https://hdl.handle.net/10356/172194 10.1016/j.sigpro.2023.108938 2-s2.0-85146681956 207 108938 en COT-V4-2019-1 Signal Processing © 2023 Elsevier B.V. All rights reserved. |
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Engineering::Electrical and electronic engineering Multichannel Active Noise Control Filtered Reference Least Mean Square Shi, Dongyuan Lam, Bhan Shen, Xiaoyi Gan, Woon-Seng Multichannel two-gradient direction filtered reference least mean square algorithm for output-constrained multichannel active noise control |
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Multichannel active noise control is a proven and long-standing technique for achieving a large zone of quiet in enclosures and open spaces. In practice, the multichannel active noise control system encounters more significant output saturation nonlinearity than the single-channel system as a result of the increased number of multiple output amplifiers, which not only degrades noise reduction performance but also compromises system stability. Conventional output-saturation solutions are mainly designed for single-channel applications, and their high computational complexity prevents them from being extended to multichannel systems. Hence, this paper proposes a novel two-gradient direction multichannel filtered reference least mean square (FxLMS) method that effectively avoids the saturation problem by restricting the output to the desired range and marginally increasing the computation over the conventional Multichannel FxLMS algorithm. In addition, this paper investigates the step sizes of the algorithm and proposes a computation-efficient variable step-size strategy to reduce further the steady-state error caused by the varying gradient directions. Finally, the efficacy of the proposed algorithm is demonstrated through numerical simulations using measured primary and secondary paths. |
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School of Electrical and Electronic Engineering |
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School of Electrical and Electronic Engineering Shi, Dongyuan Lam, Bhan Shen, Xiaoyi Gan, Woon-Seng |
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Article |
author |
Shi, Dongyuan Lam, Bhan Shen, Xiaoyi Gan, Woon-Seng |
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Shi, Dongyuan |
title |
Multichannel two-gradient direction filtered reference least mean square algorithm for output-constrained multichannel active noise control |
title_short |
Multichannel two-gradient direction filtered reference least mean square algorithm for output-constrained multichannel active noise control |
title_full |
Multichannel two-gradient direction filtered reference least mean square algorithm for output-constrained multichannel active noise control |
title_fullStr |
Multichannel two-gradient direction filtered reference least mean square algorithm for output-constrained multichannel active noise control |
title_full_unstemmed |
Multichannel two-gradient direction filtered reference least mean square algorithm for output-constrained multichannel active noise control |
title_sort |
multichannel two-gradient direction filtered reference least mean square algorithm for output-constrained multichannel active noise control |
publishDate |
2023 |
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https://hdl.handle.net/10356/172194 |
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1783955554656321536 |