A study of the characteristics of white noise using the empirical mode decomposition method

被引:1619
|
作者
Wu, ZH
Huang, NE
机构
[1] Ctr Ocean Land Atmosphere Studies, Beltsville, MD 20705 USA
[2] NASA, Goddard Space Flight Ctr, Lab Hydrospher Proc, Oceans & Ice Branch, Greenbelt, MD 20771 USA
来源
PROCEEDINGS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES | 2004年 / 460卷 / 2046期
关键词
empirical mode decomposition; intrinsic mode function; characteristics of white noise; energy-density function; energy-density spread function; statistical significance test;
D O I
10.1098/rspa.2003.1221
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Based on numerical experiments on white noise using the empirical mode decomposition (EMD) method, we find empirically that the EMD is effectively a dyadic filter., the intrinsic mode function (IMF) components are all normally distributed, and the Fourier spectra of the IMF components are all identical and cover the same area, on a semi-logarithmic period scale. Expanding from these empirical findings, we further deduce that the product of the energy density of IMF and its corresponding averaged period is a constant, and that the energy-density function is chi-squared distributed. Furthermore, we derive the energy-density spread function of the IMF components. Through these results, we establish a, method of assigning statistical significance of information content for IMF components from any noisy data. Southern Oscillation Index data, are used to illustrate the methodology developed here.
引用
收藏
页码:1597 / 1611
页数:15
相关论文
共 50 条
  • [41] An improved empirical mode decomposition method using second generation wavelets interpolation
    Wang, Jianlin
    Wei, Qingxuan
    Zhao, Liqiang
    Yu, Tao
    Han, Rui
    DIGITAL SIGNAL PROCESSING, 2018, 79 : 164 - 174
  • [42] A robust method for parameter estimation of AR systems using empirical mode decomposition
    Md. Kamrul Hasan
    M. Shakib Apu
    Md. Khademul Islam Molla
    Signal, Image and Video Processing, 2010, 4 : 451 - 461
  • [43] DATA AUGMENTATION USING EMPIRICAL MODE DECOMPOSITION ON NEURAL NETWORKS TO CLASSIFY IMPACT NOISE IN VEHICLE
    Nam, Gue-Hwan
    Bu, Seok-Jun
    Park, Na-Mu
    Seo, Jae-Yong
    Jo, Hyeon-Cheol
    Jeong, Won-Tae
    2020 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, 2020, : 731 - 735
  • [44] Empirical Mode Decomposition using the Second Derivative
    Park, Min-Su
    Kim, Donghoh
    Oh, Hee-Seok
    KOREAN JOURNAL OF APPLIED STATISTICS, 2013, 26 (02) : 335 - 347
  • [45] Noise-reduction for fringe analysis using the empirical mode decomposition with the generalized analysis model
    Su, Wei-Hung
    Lee, Chao-Kuei
    Lee, Chen-Wei
    OPTICS AND LASERS IN ENGINEERING, 2010, 48 (02) : 212 - 217
  • [46] Lung-Heart Sound Separation Using Noise Assisted Multivariate Empirical Mode Decomposition
    Lin, ChingShun
    Tanumihardja, Wisena A.
    Shih, HongHui
    2013 INTERNATIONAL SYMPOSIUM ON INTELLIGENT SIGNAL PROCESSING AND COMMUNICATIONS SYSTEMS (ISPACS), 2013, : 726 - 730
  • [47] Improved Empirical Mode Decomposition Using Optimal Recursive Averaging Noise Estimation for Speech Enhancement
    Asma Bouchair
    Sid Ahmed Selouani
    Abderrahmane Amrouche
    Mohammed Sidi Yakoub
    Circuits, Systems, and Signal Processing, 2022, 41 : 196 - 223
  • [48] Using Empirical Mode Decomposition for Ground Filtering
    Ozcan, Abdullah H.
    Unsalan, Cem
    2015 7TH INTERNATIONAL CONFERENCE ON RECENT ADVANCES IN SPACE TECHNOLOGIES (RAST), 2015, : 317 - 321
  • [49] Improved Empirical Mode Decomposition Using Optimal Recursive Averaging Noise Estimation for Speech Enhancement
    Bouchair, Asma
    Selouani, Sid Ahmed
    Amrouche, Abderrahmane
    Sidi Yakoub, Mohammed
    CIRCUITS SYSTEMS AND SIGNAL PROCESSING, 2022, 41 (01) : 196 - 223
  • [50] ECG Noise Reduction Using Empirical Mode Decomposition Based on Combination of Instantaneous Half Period and Soft-Thresholding
    Samadi, Shamim
    Shamsollahi, Mohammad B.
    2014 MIDDLE EAST CONFERENCE ON BIOMEDICAL ENGINEERING (MECBME), 2014, : 244 - 248