A new variable spatial regularized FxLMS algorithm for diffusion active noise control

Chu, Yu–Cheng; Mak, Cheuk Ming; Wu, Ming; Jie, Wu; Zhao, Yong

doi:10.1016/j.apacoust.2023.109532

Cited by 4 publications

(1 citation statement)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Hence, the local active noise control technology represented by active noise reduction headrests is flourishing. It has also found applications in scenarios such as automotive road noise control and aircraft cabin noise control, and related research is constantly being deepened [4][5][6][7].…”

Section: Introductionmentioning

confidence: 99%

Dynamic Matching of Reconstruction and Anti-Aliasing Filters in Adaptive Active Noise Control

Zhang,

Wu,

Wang

et al. 2024

Applied Sciences

View full text Add to dashboard Cite

Constrained by the computing power, adaptive active noise control systems often have a low sampling rate. Therefore, reconstruction filters and anti-aliasing filters with fixed parameters are generally adopted to eliminate the mirror noise and aliasing noise, respectively; however, they may boost the group delay of the system. A dynamic matching method based on dual sampling rates is proposed to dynamically adjust the parameters of the reconstruction and anti-aliasing filters, according to the characteristics of the primary sound source, for a compromise between high-frequency noise and group delay. In digital high-sampling-rate regions, data that include high-frequency information are analyzed regularly, following which the parameters of the reconstruction filters and those of the anti-aliasing filters are dynamically matched. In digital low-sampling-rate regions, the estimation of the secondary path transfer function is updated. The results of laboratory experiments show that the proposed method not only can suppress the mirror and aliasing noise for primary sound sources with different spectra, but can also effectively reduce the group delay and improve the noise reduction performance of a system.

show abstract

Section: Introductionmentioning

confidence: 99%