Wavelet ridge diagnosis of time-varying elliptical signals with application to an oceanic eddy

被引:51
|
作者
Lilly, J. M. [1 ]
Gascard, J. -C. [1 ]
机构
[1] Univ Paris 06, Lab Oceanog Dynam & Climatol, Paris, France
关键词
D O I
10.5194/npg-13-467-2006
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
A method for diagnosing the physical properties of a time-varying ellipse is presented. This essentially involves extending the notion of instantaneous frequency to the bivariate case. New complications, and possibilities, arise from the fact that there are several meaningful forms in which a time-varying ellipse may be represented. A perturbation analysis valid for the near-circular case clarifies these issues. Diagnosis of the ellipse properties may then be performed using wavelet ridge analysis, and slowly-varying changes in the ellipse structure may be decoupled from the fast orbital motion through the use of elliptic integrals, without the need for additional explicit filtering. The theory is presented in parallel with an application to a position time series of a drifting subsurface float trapped in an oceanic eddy.
引用
收藏
页码:467 / 483
页数:17
相关论文
共 50 条
  • [1] Power system time-varying oscillation analysis with wavelet ridge algorithm
    Zhang, Pengfei
    Xue, Yusheng
    Zhang, Qiping
    Dianli Xitong Zidonghua/Automation of Electric Power Systems, 2004, 28 (16): : 32 - 35
  • [2] Analysis of time-varying signals using continuous wavelet and synchrosqueezed transforms
    Tary, Jean Baptiste
    Herrera, Roberto Henry
    van der Baan, Mirko
    PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES, 2018, 376 (2126):
  • [3] Correlation analysis of time-varying signals by the wavelet obtained from measurement
    Ishimitsu, S
    Kitagawa, H
    Hagino, N
    Horihata, S
    NOISE AND VIBRATION ENGINEERING, VOLS 1 - 3, PROCEEDINGS, 2001, : 945 - 949
  • [4] Modeling of nonstationary signals based on time-varying autoregression and its application in fault diagnosis of bearing
    Wang, Guo-Feng
    Luo, Zhi-Gao
    Qin, Xu-Da
    Leng, Yong-Gang
    Chang, Le
    Tianjin Daxue Xuebao (Ziran Kexue yu Gongcheng Jishu Ban)/Journal of Tianjin University Science and Technology, 2008, 41 (05): : 558 - 562
  • [5] Parameter identification of time-varying structures by using wavelet ridge extraction and adaptive filtering
    Zhang J.
    Shi Z.-Y.
    Zhendong Gongcheng Xuebao/Journal of Vibration Engineering, 2019, 32 (03): : 462 - 470
  • [6] The classification of transient time-varying EEG signals via wavelet packets decomposition
    Shen, MF
    Sun, LS
    Chan, FHY
    8TH INTERNATIONAL CONFERENCE ON NEURAL INFORMATION PROCESSING, VOLS 1-3, PROCEEDING, 2001, : 1289 - 1293
  • [7] Parametric time-varying spectrum audits application to SEMG signals
    Korosec, D
    MEDICAL INFORMATICS EUROPE '99, 1999, 68 : 385 - 390
  • [8] Classification of transient time-varying signals using DFT and wavelet packet based methods
    Delfs, C
    Jondral, F
    PROCEEDINGS OF THE 1998 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING, VOLS 1-6, 1998, : 1569 - 1572
  • [9] Estimating information in time-varying signals
    Cepeda-Humerez, Sarah Anhala
    Ruess, Jakob
    Tkacik, Gasper
    PLOS COMPUTATIONAL BIOLOGY, 2019, 15 (09)
  • [10] COMPRESSED SENSING OF TIME-VARYING SIGNALS
    Angelosante, D.
    Giannakis, G. B.
    Grossi, E.
    2009 16TH INTERNATIONAL CONFERENCE ON DIGITAL SIGNAL PROCESSING, VOLS 1 AND 2, 2009, : 816 - +