FxLMS/F Based Tap Decomposed Adaptive Filter for Decentralized Active Noise Control System

IF 4.1 2区计算机科学 Q1 ACOUSTICS

IEEE/ACM Transactions on Audio, Speech, and Language Processing Pub Date : 2024-10-31 DOI:10.1109/TASLP.2024.3473294

Munukutla L. N. Srinivas Karthik;Joel S.;Nithin V. George

引用次数: 0

Abstract

Decentralized systems are appealing due to their reduced complexity and flexibility. A class of decentralized multi-channel active noise control (MCANC) systems has been developed in this paper. In the first part of the study, a modified filtered-x least mean square/fourth (FxLMS/F) algorithm, which offers improved noise reduction performance over the conventional FxLMS/F algorithm, was developed for MCANC. Further, to reduce the computational complexity of the proposed MCANC system, a nearest Kronecker product (NKP) decomposition strategy has been incorporated to develop decentralized versions of FxLMS/F algorithms. The proposed algorithms have been shown to offer enhanced noise reduction at reduced computational complexity when applied for noise control for narrowband noise, bandlimited white noise, traffic noise and wind noise.

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基于 FxLMS/F 的分接分解自适应滤波器用于分散式主动噪声控制系统

分散式系统因其复杂性和灵活性较低而颇具吸引力。本文开发了一类分散式多通道有源噪声控制系统（MCANC）。在研究的第一部分，为 MCANC 开发了一种改进的滤波-x 最小均方/四次方（FxLMS/F）算法，与传统的 FxLMS/F 算法相比，该算法具有更好的降噪性能。此外，为了降低拟议 MCANC 系统的计算复杂度，还采用了最近克朗克积（NKP）分解策略来开发分散版本的 FxLMS/F 算法。在应用于窄带噪声、带限白噪声、交通噪声和风噪声的噪声控制时，已证明所提出的算法能在降低计算复杂度的同时增强降噪效果。

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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来源期刊

IEEE/ACM Transactions on Audio, Speech, and Language Processing ACOUSTICS-ENGINEERING, ELECTRICAL & ELECTRONIC

CiteScore

11.30

自引率

11.10%

发文量

217

期刊介绍： The IEEE/ACM Transactions on Audio, Speech, and Language Processing covers audio, speech and language processing and the sciences that support them. In audio processing: transducers, room acoustics, active sound control, human audition, analysis/synthesis/coding of music, and consumer audio. In speech processing: areas such as speech analysis, synthesis, coding, speech and speaker recognition, speech production and perception, and speech enhancement. In language processing: speech and text analysis, understanding, generation, dialog management, translation, summarization, question answering and document indexing and retrieval, as well as general language modeling.