算法
噪音(视频)
计算机科学
理论(学习稳定性)
趋同(经济学)
主动噪声控制
节点(物理)
最小均方滤波器
人工智能
降噪
机器学习
自适应滤波器
工程类
结构工程
经济
图像(数学)
经济增长
作者
Tianyou Li,Siyuan Lian,Sipei Zhao,Jing Lü,Lee Burnett
出处
期刊:IEEE/ACM transactions on audio, speech, and language processing
[Institute of Electrical and Electronics Engineers]
日期:2023-01-01
卷期号:31: 1449-1463
被引量:12
标识
DOI:10.1109/taslp.2023.3261742
摘要
Multichannel active noise control (ANC) systems have been widely investigated for low-frequency noise attenuation over a spatial region. Using a conventional centralized control strategy based on the multichannel filtered- x least mean square (F x LMS) algorithm has been demonstrated to be effective for multichannel ANC systems, but the high computational burden restricts its practical applications. Meanwhile, a decentralized control strategy suffers from stability problems although it has been successful in reducing the computational load. Recently, distributed control strategies, such as the multitask diffusion adaptation scheme, have been introduced to ANC systems and shown to mitigate the stability problems in decentralized systems. However, distributed ANC systems using the diffusion F x LMS algorithm require strong symmetry of acoustic paths because of the dependence on node-based adaptation and neighborhood-based combination. To overcome this limitation, this paper proposes an Augmented Diffusion F x LMS algorithm with neighborhood-based adaptation and node-based combination. A theoretical formulation and convergence analysis are presented and simulations are performed to compare the proposed algorithm with existing ones under different system configurations for tonal, multi-tonal, narrowband and broadband signals. Simulation results demonstrate that the proposed algorithm has the same noise reduction performance as centralized method even if the acoustic paths are strongly asymmetrical, which is superior over existing distributed multitask diffusion strategy.
科研通智能强力驱动
Strongly Powered by AbleSci AI