3 papers
eess.SP2026
A Novel Monte Carlo Gradient Method Based on Meta-learning for Effective Step-size Selection in Active Noise Control
Luyuan Li, Jisheng Bai, Xiruo Su +3
Active noise control (ANC) is an effective approach to noise suppression, and the filtered-reference least mean square (FxLMS) algorithm is a widely adopted method in ANC systems,…
eess.SY2024
Preventing output saturation in active noise control: An output-constrained Kalman filter approach
Junwei Ji, Dongyuan Shi, Boxiang Wang +3
The Kalman filter (KF)-based active noise control (ANC) system demonstrates superior tracking and faster convergence compared to the least mean square (LMS) method, particularly in…
eess.SP2024
Transferable Selective Virtual Sensing Active Noise Control Technique Based on Metric Learning
Boxiang Wang, Dongyuan Shi, Zhengding Luo +3
Virtual sensing (VS) technology enables active noise control (ANC) systems to attenuate noise at virtual locations distant from the physical error microphones. Appropriate auxiliar…