Multi-channel normalized FxLMS algorithm for active noise control

被引:4
|
作者
Chung, Ik Joo [1 ]
机构
[1] Kangwon Natl Univ, Dept Elect & Elect Engn, 1 Kangwondaehak Gil, Chunchon 24341, Gangwon, South Korea
来源
关键词
FxLMS (Filtered-x Least Mean Square); Multi-channel normalized FxLMS; Active noise control;
D O I
10.7776/ASK.2016.35.4.280
中图分类号
O42 [声学];
学科分类号
070206 ; 082403 ;
摘要
In this paper, we propose a normalization algorithm that can be applied to adaptive filters for multi-channel active noise control. The FxLMS (Filtered-x Least Mean Square) algorithm for the single-channel active noise control can be normalized in the same way as the NLMS (Normalized Least Mean Square) algorithm, whereas in case of the multi-channel active noise control, the single-channel normalization for the FxLMS algorithm cannot be extended to the normalization for the multi-channel FxLMS algorithm straightforwardly. First, we adopt a generalized normalization algorithm for the multi-channel FxLMS algorithm based on the principle of minimal disturbance and then, proposed a normalized algorithm considering only diagonal elements to avoid computation for matrix inversion. We carried out performance comparisons of the proposed algorithm with other algorithms without normalization. It is shown that the proposed algorithm presents better convergence characteristics under non-stationary environments.
引用
收藏
页码:280 / 287
页数:8
相关论文
共 50 条
  • [41] Nonlinear FXLMS algorithm for active noise control systems with saturation nonlinearity
    Sahib, Mouayad A.
    Kamil, Raja
    Marhaban, Mohammad H.
    IEEJ TRANSACTIONS ON ELECTRICAL AND ELECTRONIC ENGINEERING, 2012, 7 (06) : 598 - 606
  • [42] An Intermittent FxLMS Algorithm for Active Noise Control Systems With Saturation Nonlinearity
    Tian, Xing
    Huang, Jie
    Feng, Xuelei
    Shen, Yong
    IEEE/ACM Transactions on Audio Speech and Language Processing, 2022, 30 : 2347 - 2356
  • [43] Deep MCANC: A deep learning approach to multi-channel active noise control
    Zhang, Hao
    Wang, DeLiang
    NEURAL NETWORKS, 2023, 158 : 318 - 327
  • [44] Application of multi-channel hybrid active noise control systems for infant incubators
    Liu, Lichuan
    Beemanpally, Kaplia
    Kuo, Sen M.
    NOISE CONTROL ENGINEERING JOURNAL, 2013, 61 (02) : 169 - 179
  • [45] Simulation of Multi-channel Active Noise Control Based on Dynamic Neural Network
    Wang, Bing
    Zi, Keming
    ADVANCED MECHANICAL DESIGN, PTS 1-3, 2012, 479-481 : 1293 - 1296
  • [46] A study on multi-channel active sound profiling algorithm for hybrid control of broadband and narrowband noise inside vehicles
    Liu, Xuexian
    Zheng, Xu
    Jia, Zibin
    Li, Rubin
    Wan, Bo
    Liu, Chi
    Qiu, Yi
    MEASUREMENT, 2024, 237
  • [47] Enhanced Multi-Channel Active Fuzzy Neural Network Noise Control in an Enclosure
    Azadi, Navid
    Ohadi, Abdolreza
    WORLD CONGRESS ON ENGINEERING, WCE 2011, VOL III, 2011, : 2532 - 2536
  • [48] Multi-channel Real Time Active Noise Control System for Infant Incubators
    Liu, Lichuan
    Gujjula, Shruthi
    Kuo, Sen M.
    2009 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-20, 2009, : 935 - 938
  • [49] Online multi-channel secondary path modeling in active noise control without auxiliary noise
    Hu, Meiling
    Xue, Jinpei
    Lu, Jing
    JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA, 2019, 146 (04): : 2590 - 2595
  • [50] A weight-constrained FxLMS algorithm for feedforward active noise control systems
    Lan, H
    Zhang, M
    Ser, W
    IEEE SIGNAL PROCESSING LETTERS, 2002, 9 (01) : 1 - 4