1. Feedforward selective fixed-filter active noise control : algorithm and implementation
- Author
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Bhan Lam, Shulin Wen, Woon-Seng Gan, Dongyuan Shi, and School of Electrical and Electronic Engineering
- Subjects
Acoustics and Ultrasonics ,Computer science ,Noise reduction ,Feature extraction ,Automatic frequency control ,Feed forward ,Response time ,Least mean squares filter ,030507 speech-language pathology & audiology ,03 medical and health sciences ,Computational Mathematics ,Active Noise Control ,Robustness (computer science) ,Computer Science (miscellaneous) ,Electrical and electronic engineering [Engineering] ,Selective Fixed-filter Active Noise Control ,Electrical and Electronic Engineering ,0305 other medical science ,Algorithm ,Active noise control - Abstract
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 pre-trained 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 nonstationary disturbance. NRF (Natl Research Foundation, S’pore) Accepted version
- Published
- 2020