Robust Sparse Multichannel Active Noise Control
Date
2019
Authors
Xie, Jingli
Jin, Danqi
Zhang, Wen
Zhang, Xiao-Lei
Chen, Jie
Wang, DeLiang
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Volume Title
Publisher
IEEE
Abstract
Multichannel active noise control (MC-ANC) aims to cancel low-frequency noise in an enclosure. If noise sources are distributed sparsely in space, adding an `1-norm constraint to the standard MC-ANC helps to reduce the complexity of the system and accelerate the convergence rate. However, the convergence performance of `1-norm constrained MCANC
(c`1-MC-ANC) degrades significantly in reverberant
environments. In this paper, we analyze the necessity of using sparsity-inducing algorithms with distinct zero-attracting strengths over loudspeakers, and then derive three algorithms of this kind in the complex domain. Simulation results show
that, compared to c`1-MC-ANC, the proposed algorithms exhibit faster convergence or higher noise reduction at steady state in both free field and reverberant environments
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Conference paper
Book Title
44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019
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2037-12-31
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