2021 IEEE International Conference on Acoustics, Speech and Signal Processing

6-11 June 2021 • Toronto, Ontario, Canada

Extracting Knowledge from Information

2021 IEEE International Conference on Acoustics, Speech and Signal Processing

6-11 June 2021 • Toronto, Ontario, Canada

Extracting Knowledge from Information
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Paper Detail

Paper IDSAM-13.3
Paper Title A Diffusion FxLMS Algorithm for Multi-Channel Active Noise Control and Variable Spatial Smoothing
Authors Yijing Chu, South China University of Technology, China; S. C. Chan, University of Hong Kong, China; C. M. Mak, The Hong Kong Polytechnic University, China; Ming Wu, Chinese Academy of Sciences, China
SessionSAM-13: Multi-Channel Data Fusion and Processing
LocationGather.Town
Session Time:Friday, 11 June, 14:00 - 14:45
Presentation Time:Friday, 11 June, 14:00 - 14:45
Presentation Poster
Topic Sensor Array and Multichannel Signal Processing: [SAM-APPL] Applications of sensor & array multichannel processing
IEEE Xplore Open Preview  Click here to view in IEEE Xplore
Abstract This paper studies the diffusion (Diff) control for multi-channel ANC systems, where a group of controllers and error microphones are physically distributed at different locations within a large area. In this case, the conventional consensus agreement for controllers cannot be reached. To solve this problem, a new Diff filtered-x least mean squares (Diff-FxLMS) algorithm that incorporates the knowledge of spatial smoothness is proposed. Compared to conventional Diff control criteria that have a fixed spatial smoothing strategy, the proposed Diff-FxLMS adjusts a so called spatial regularization (SR) coefficient adaptively such that the neighboring controllers keep their decision variables close to one another to minimize the global cost function while giving preference to possibly distinct local signals. A detailed performance analysis is carried out and verified by simulation. Based on the analysis, a variable SR formula is derived. The performance of the proposed algorithm is also compared with conventional methods.