论文标题
基于后传播机制的多通道主动噪声控制的实施
Implementation of Multi-channel Active Noise Control based on Back-propagation Mechanism
论文作者
论文摘要
主动噪声控制（ANC）系统可以通过引入反噪声与不需要的噪声结合使用来有效地减弱低频噪声。在ANC系统中，滤波的最小成方（FXLM）和过滤的X归一化最小均值（FXNLMS）算法是自适应调节控制过滤器的众所周知的算法。通常需要多通道ANC系统在大空间中衰减不需要的噪音。但是，多渠道FXLM（MCFXLM）和多频道FXNLMS（MCFXNLMS）算法的开源实现仍然稀缺。因此，本文提出了MCFXLM和MCFXNLMS算法的简单有效实施方法。在神经网络训练期间的后传播过程中，MCFXLM和MCFXNLMS算法可以通过自动推导机制实现。我们使用Pytorch中的自动推导机制实现了两种算法，并在GitHub上提供了源代码。这种实现方法可以改善多通道ANC系统的实用性，该系统预计将在ANC应用中广泛使用。
Active noise control (ANC) systems can efficiently attenuate low-frequency noises by introducing anti-noises to combine with the unwanted noises. In ANC systems, the filtered-x least mean square (FxLMS) and filtered-X normalized least-mean-square (FxNLMS) algorithm are well-known algorithms for adaptively adjusting control filters. Multi-channel ANC systems are typically required to attenuate unwanted noises in a large space. However, open-source implementations of the multi-channel FxLMS (McFxLMS) and multi-channel FxNLMS (McFxNLMS) algorithm continue to be scarce. Therefore, this paper proposes a simple and effective implementation approach of the McFxLMS and McFxNLMS algorithm. Motivated by the back-propagation process during neural network training, the McFxLMS and McFxNLMS algorithm can be implemented via automatic derivation mechanism. We implemented the two algorithms using the automatic derivation mechanism in PyTorch and made the source code available on GitHub. This implementation method can improve the practicality of multi-channel ANC systems, which is expected to be widely used in ANC applications.
