Singularity study of underwater acoustic signals with wavelet transform

被引：0
|
作者：
Zhang, X.L. [1 ]
Sun, J.C. [1 ]
机构：
[1] Coll. of Marine Eng., Northwestern Polytech. Univ., Xi'an 710072, China
来源：
Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University | 2000年 / 18卷 / 04期
关键词：
Classification (of information) - Feature extraction - Pattern recognition - Wavelet transforms;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
The key to a underwater target recognition and classification is a feature extraction. It was proposed that the Lipschitz singularity exponent of the underwater acoustic signal is considered as the feature parameter of target recognition. The relationship between wavelet transform and Lipschitz exponent was discussed. The base functions of wavelet transform were selected based on the vanishing moment requirement. Simulation results show that for different acoustic signal, the corresponding energy Lipschitz exponents are distributed over different ranges.
引用
收藏
页码：608 / 611
相关论文
共 50 条
  • [21] A wavelet transform based contrast enhancement method for underwater acoustic images
    R. Priyadharsini
    T. Sree Sharmila
    V. Rajendran
    Multidimensional Systems and Signal Processing, 2018, 29 : 1845 - 1859
  • [22] Study on Wavelet Transform in the Processing for ECG Signals
    Tan Yun-fu
    Du Lei
    2009 WRI WORLD CONGRESS ON SOFTWARE ENGINEERING, VOL 4, PROCEEDINGS, 2009, : 515 - 518
  • [23] Automated peak decomposition of evoked potential signals using wavelet transform singularity detection
    McCooey, Conor G.
    Kumar, Dinesh
    2007 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-16, 2007, : 1920 - 1923
  • [24] Study on the Effects of the Wavelet Transform-based Air Compartment on the Decay Pattern of Underwater Explosion Signals
    Jia Hu
    Shen Zhaowu
    Ma Honghao
    Fan Zijian
    PROGRESS IN SAFETY SCIENCE AND TECHNOLOGY, VOL. VIII, PTS A AND B, 2010, 8 : 1118 - 1123
  • [25] Study on blind separation of underwater acoustic signals
    Zhang, XH
    Zhang, AQ
    Fang, JP
    Yang, SQ
    2000 5TH INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING PROCEEDINGS, VOLS I-III, 2000, : 1802 - 1805
  • [26] Estimation of the tool condition by applying the wavelet transform to acoustic emission signals
    Gomez, M. P.
    Piotrkowski, R.
    Ruzzante, J. E.
    D'Attellis, C. E.
    Review of Progress in Quantitative Nondestructive Evaluation, Vols 26A and 26B, 2007, 894 : 635 - 641
  • [27] Wavelet packet transform for detection of single events in acoustic emission signals
    Bianchi, Davide
    Mayrhofer, Erwin
    Groeschl, Martin
    Betz, Gerhard
    Vernes, Andras
    MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2015, 64-65 : 441 - 451
  • [28] Strength Evaluation of Stomatologic Polymers by Wavelet Transform of Acoustic Emission Signals
    Skal's'kii, V. R.
    Makeev, V. F.
    Stankevich, O. M.
    Kyrmanov, O. S.
    Vynnyts'ka, S. I.
    Opanasovich, V. K.
    STRENGTH OF MATERIALS, 2015, 47 (04) : 566 - 572
  • [29] De-Noising Signals Using Wavelet Transform in Internet of Underwater Things
    Khan, Asiya
    Pemberton, Richard
    Momen, Abdul
    Bristow, Daniel
    INTELLIGENT SYSTEMS AND APPLICATIONS, VOL 2, 2020, 1038 : 1192 - 1198
  • [30] Strength Evaluation of Stomatologic Polymers by Wavelet Transform of Acoustic Emission Signals
    V. R. Skal’s’kii
    V. F. Makeev
    O. M. Stankevich
    O. S. Kyrmanov
    S. I. Vynnyts’ka
    V. K. Opanasovich
    Strength of Materials, 2015, 47 : 566 - 572
12345