A Novel Minimax Algorithm for Multi-channel Active Noise Control System

M. Jain, Arun Kumar, R. Bahl
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引用次数: 1

Abstract

Global active noise control (ANC) employs multichannel filtered-x least mean square (MCFxLMS) algorithm as it is more suitable algorithm to obtain large quiet zone. Minimax algorithm was proposed to counter the higher computational complexity faced in MCFxLMS based ANC by minimizing the square of the maximum of the absolute values of residual noise at the error microphones. However, the minimax approach leads to inferior performance in terms of convergence as well as noise reduction. Also, the classical minimax approach offers little flexibility in adjusting the ANC performance. In this paper, a novel minimax algorithm is proposed in order to tackle these shortcomings of conventional minimax algorithm at a cost of increase in computational complexity as compared to conventional minimax algorithm. The performance of the proposed approach is evaluated and compared with classical minimax for global noise reduction in a 2-dimensional quiet zone of size 1 m x 1 m in a 3-dimensional reverberant room. The proposed scheme is able to improve the performance with much reduced computational complexity as compared to MCFxLMS though with increased computational complexity as compared to classical minimax approach.
一种新的多通道有源噪声控制的极大极小算法
全局主动噪声控制(ANC)采用多通道滤波-x最小均方(MCFxLMS)算法,因为该算法更适合获得大的安静区。针对基于MCFxLMS的自适应自适应算法计算复杂度较高的问题,提出了最小化误差传声器处残余噪声绝对值最大值平方的算法。然而,极大极小方法在收敛性和降噪方面的性能较差。此外,经典的极大极小方法在调整ANC性能方面提供的灵活性很小。本文提出了一种新的极大极小算法,以克服传统极大极小算法的这些缺点,但与传统极大极小算法相比,其计算复杂度有所增加。在三维混响室内尺寸为1 m × 1 m的二维安静区中,对所提出的方法的性能进行了评估,并与经典的极大极小值方法进行了比较。与MCFxLMS相比,该方案能够以大大降低的计算复杂度提高性能,但与经典的极大极小方法相比,该方案的计算复杂度有所增加。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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