From the 1 of 9 linked papers with an AI index.
9 papers
Adaptive Momentum Enhanced Distributed Multichannel Active Noise Control for Faster Convergence under Communication Delays
Junwei Ji, Woon-Seng Gan, Boxiang Wang +2
Distributed multichannel active noise control (DMCANC) reduces the computational burden of centralized ANC systems by distributing processing tasks across multiple nodes, while req…
Spatial-Frequency Cued Generative Fixed-Filter Active Noise Control Based on Deep Learning in Reverberant Environments
Boxiang Wang, Haowen Li, Dongyuan Shi +4
The paper introduces a spatial‑frequency cued generative fixed‑filter active noise control (SF‑GFANC) system that uses a multi‑task CRNN to estimate 3D source location and filter c…
Predictive Fixed-Filter Active Noise Control (PFANC) Using Convolutional Recurrent Neural Networks for Dynamic Noises
Zhengding Luo, Haowen Li, Haozhe Ma +3
The existing Generative Fixed-Filter Active Noise Control (GFANC) method generates a suitable control filter based on the current noise frame. This reactive design aims to estimate…
Distributed Multichannel Active Noise Control with Asynchronous Communication
Junwei Ji, Dongyuan Shi, Boxiang Wang +3
Distributed multichannel active noise control (DMCANC) offers effective noise reduction across large spatial areas by distributing the computational load of centralized control to…
Directional Selective Fixed-Filter Active Noise Control Based on a Convolutional Neural Network in Reverberant Environments
Boxiang Wang, Zhengding Luo, Haowen Li +4
Selective fixed-filter active noise control (SFANC) is a novel approach capable of mitigating noise with varying frequency characteristics. It offers faster response and greater co…
DOA Estimation with Lightweight Network on LLM-Aided Simulated Acoustic Scenes
Haowen Li, Zhengding Luo, Dongyuan Shi +4
Direction-of-Arrival (DOA) estimation is critical in spatial audio and acoustic signal processing, with wide-ranging applications in real-world. Most existing DOA models are traine…