噪音(视频)
人工神经网络
最小均方滤波器
主动噪声控制
计算机科学
控制理论(社会学)
降噪
算法
控制(管理)
非线性系统
人工智能
自适应滤波器
物理
量子力学
图像(数学)
作者
Lu Lu,Kaili Yin,Rodrigo C. de Lamare,Zongsheng Zheng,Yi Yu,Xiaomin Yang,Badong Chen
标识
DOI:10.1016/j.sigpro.2021.108039
摘要
Active noise control (ANC) is an effective way for reducing the noise level in electroacoustic or electromechanical systems. Since its first introduction in 1936, this approach has been greatly developed. This paper focuses on discussing the development of ANC techniques over the past decade. Linear ANC algorithms, including the celebrated filtered-x least-mean-square (FxLMS)-based algorithms and distributed ANC algorithms, are investigated and evaluated. Nonlinear ANC (NLANC) techniques, such as functional link artificial neural network (FLANN)-based algorithms, are pursued in Part II. Furthermore, some novel methods and applications of ANC emerging in the past decade are summarized. Finally, future research challenges regarding the ANC technique are discussed.
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