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 microphones often presents challenges due to physical limitations. Virtual sensing technique that effectively suppresses the noise far from the physical error microphones is one of the most promising solutions. Nevertheless, the conventional multichannel virtual sensing ANC (MVANC) system based on the multichannel filtered reference least mean square (MCFxLMS) algorithm often suffers from high computational complexity. This paper proposes a feedforward MVANC system that incorporates the multichannel adjoint least mean square (MCALMS) algorithm to overcome these limitations effectively. Computational analysis demonstrates the improvement of computational efficiency and numerical simulations exhibit comparable noise reduction performance at virtual locations compared to the conventional MCFxLMS algorithm. Additionally, the effects of varied tuning noises on system performance are also investigated, providing insightful findings on optimizing MVANC systems.
Code (0)
등록된 구현이 없습니다.
Tasks
Computational EfficiencySimilar Papers 제목 키워드 기반
Implementation of the Feedforward Multichannel Virtual Sensing Active Noise Control (MVANC) by Using MATLAB
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 from the physical error microphones…
Implementation of the Multichannel Filtered Reference Least Mean Square (McFxLMS) Algorithm with an Arbitrary Number of Channels by Using MATLAB
Multichannel filtered reference least mean square (McFxLMS) algorithms are widely utilized in adaptive multichannel active noise control (MCANC) applications. As a critical and high-computationally efficient adaptive cri…
Active Noise Control based on the Momentum Multichannel Normalized Filtered-x Least Mean Square Algorithm
Multichannel active noise control (MCANC) is widely utilized to achieve significant noise cancellation area in the complicated acoustic field. Meanwhile, the filter-x least mean square (FxLMS) algorithm gradually becomes…
Spatiotemporal Sparse Bayesian Learning with Applications to Compressed Sensing of Multichannel Physiological Signals
Energy consumption is an important issue in continuous wireless telemonitoring of physiological signals. Compressed sensing (CS) is a promising framework to address it, due to its energy-efficient data compression proced…
Brain Computer Interfacecompressed sensingData CompressionEEG+1Data-aided Sensing for Gaussian Process Regression in IoT Systems
In this paper, for efficient data collection with limited bandwidth, data-aided sensing is applied to Gaussian process regression that is used to learn data sets collected from sensors in Internet-of-Things systems. We f…
regression