.png){kind=icon}
Return
Feedforward Selective Fixed-Filter Active Noise Control: Algorithm and Implementation
.png){kind=icon}
OA
AI
DOI：10.1109/TASLP.2020.2989582.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Conventional real-time active noise control (ANC) usually employs the adaptive filtered-x least mean square (FxLMS) algorithm to approach optimum coefficients for the control filter. However, lengthy training is usually required, and the perceived noise reduction is not immediately realized. Motivated by the practical implementation, we propose a selective fixed-filter active noise control (SFANC) algorithm, which selects a pretrained control filter to attenuate the detected primary noise rapidly. On top of improved robustness, the complexity analysis reveals that SFANC appears to be more efficient. The SFANC algorithm chooses the most suitable control filter based on the frequency-band-match approach implemented in a partitioned frequency-domain filter. Through simulations, SFANC is shown to exhibit a satisfactory response time and steady-state noise reduction performance, even for time-varying noise and real non-stationary disturbance.
Keywords:
Training
Optimized production technology
Frequency control
Feature extraction
Noise reduction
Speech processing
Signal processing algorithms
Active noise control
selective fixed-filter active noise control
frequency-domain filtering
filtered-x least mean square
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
I
IF:
5.1
Papers:
2.6K
Citations:
1.1W
Organization
Cited Papers
ShareSave
ShareSaveIntegrated active noise control for open-fit hearing aids with customized filter.png)
APPLIED ACOUSTICS
APPLIED ACOUSTICSIF3.6
PREAI
ShareSaveShareSaveShareSaveShareSavePhysical limits on the performance of active noise control through open windowsAPPLIED ACOUSTICSOAAI
APPLIED ACOUSTICSIF3.6
OAAIShareSave
View more