Active noise control

Adaptive filter

Noise control

Control engineering

Noise reduction

Mathematics

Feed forward

Noise (video)

Gene

Algorithm

Image (mathematics)

Filter (signal processing)

Reduction (mathematics)

Engineering

Artificial intelligence

Control (management)

Chemistry

Geometry

Computer science

Computer vision

Least mean squares filter

Control theory (sociology)

Biochemistry

Robustness (evolution)

IEEE/ACM Transactions on Audio Speech and Language Processing

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.

Feedforward Selective Fixed-filter Active Noise Control: Algorithm and Implementation