What is behind the meta-learning initialization of adaptive filter?—a naive method for accelerating convergence of adaptive multichannel active noise control
Active noise control (ANC) is a typical signal-processing technique that has recently been
utilized extensively to combat the urban noise problem. Although numerous advanced …
utilized extensively to combat the urban noise problem. Although numerous advanced …
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 …
Unsupervised learning based end-to-end delayless generative fixed-filter active noise control
Delayless noise control is achieved by our earlier generative fixed-filter active noise control
(GFANC) framework through efficient coordination between the co-processor and real-time …
(GFANC) framework through efficient coordination between the co-processor and real-time …
Implementation of minimum output variance filtered reference least mean square algorithm with optimal time-varying penalty factor estimate to overcome output …
The minimum output variance filtered reference least mean square (MOV-FxLMS) algorithm
can effectively prevent the instability of active noise control (ANC) systems caused by the …
can effectively prevent the instability of active noise control (ANC) systems caused by the …
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 …
Point neuron learning: a new physics-informed neural network architecture
H Bi, TD Abhayapala - EURASIP Journal on Audio, Speech, and Music …, 2024 - Springer
Abstract Machine learning and neural networks have advanced numerous research
domains, but challenges such as large training data requirements and inconsistent model …
domains, but challenges such as large training data requirements and inconsistent model …
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 …