A survey on adaptive active noise control algorithms overcoming the output saturation effect
This paper presents a comparison of contemporary algorithms aimed at mitigating the
saturation-induced challenges in active noise control (ANC) systems. The saturation effect …
saturation-induced challenges in active noise control (ANC) systems. The saturation effect …
Real-time implementation and explainable AI analysis of delayless CNN-based selective fixed-filter active noise control
The selective fixed-filter active noise control (SFANC) approach can select suitable pre-
trained control filters for different types of noise. With the learning ability of convolutional …
trained control filters for different types of noise. With the learning ability of convolutional …
Gfanc-rl: Reinforcement learning-based generative fixed-filter active noise control
Abstract The recent Generative Fixed-filter Active Noise Control (GFANC) method achieves
a good trade-off between noise reduction performance and system stability. However …
a good trade-off between noise reduction performance and system stability. However …
Contrastive meta-reinforcement learning for heterogeneous graph neural architecture search
Z Xu, J Wu - Expert Systems with Applications, 2025 - Elsevier
Abstract Heterogeneous Graph Neural Networks (HGNNs) have demonstrated significant
success in capturing complex interactions within heterogeneous graphs to learn graph …
success in capturing complex interactions within heterogeneous graphs to learn graph …
Implementation of Kalman Filter Approach for Active Noise Control by Using MATLAB: Dynamic Noise Cancellation
G Yu - arXiv preprint arXiv:2402.06896, 2024 - arxiv.org
This article offers an elaborate description of a Kalman filter code employed in the active
control system. Conventional active noise management methods usually employ an …
control system. Conventional active noise management methods usually employ an …
Efficient modeling of liquid splashing via graph neural networks with adaptive filter and aggregator fusion
J Nan, P Feng, J Xu, F Feng - … Journal of Numerical Methods for Heat …, 2024 - emerald.com
Purpose The purpose of this study is to advance the computational modeling of liquid
splashing dynamics, while balancing simulation accuracy and computational efficiency, a …
splashing dynamics, while balancing simulation accuracy and computational efficiency, a …
Transferable Selective Virtual Sensing Active Noise Control Technique Based on Metric Learning
Virtual sensing (VS) technology enables active noise control (ANC) systems to attenuate
noise at virtual locations distant from the physical error microphones. Appropriate auxiliary …
noise at virtual locations distant from the physical error microphones. Appropriate auxiliary …
Implementation of the Feedforward Multichannel Virtual Sensing Active Noise Control (MVANC) by Using MATLAB
B Wang - arXiv preprint arXiv:2405.10510, 2024 - arxiv.org
The multichannel virtual sensing active noise control (MVANC) methodology is an advanced
approach that may provide a wide area of silence at specific virtual positions that are distant …
approach that may provide a wide area of silence at specific virtual positions that are distant …
Computation-efficient Virtual Sensing Approach with Multichannel Adjoint Least Mean Square Algorithm
Multichannel active noise control (ANC) systems are designed to create a large zone of
quietness (ZoQ) around the error microphones, however, the placement of these …
quietness (ZoQ) around the error microphones, however, the placement of these …
Implementation of the Multichannel Filtered Reference Least Mean Square (McFxLMS) Algorithm with an Arbitrary Number of Channels by Using MATLAB
B Wang - arXiv preprint arXiv:2402.09449, 2024 - arxiv.org
Multichannel filtered reference least mean square (McFxLMS) algorithms are widely utilized
in adaptive multichannel active noise control (MCANC) applications. As a critical and high …
in adaptive multichannel active noise control (MCANC) applications. As a critical and high …