Empirical Mode Decomposition for vectorial bi-dimensional signals

被引：0
|
作者：
Azzaoui, Nourddine [1 ]
Miraoui, Abdelkader [1 ]
Snoussi, Hichem [1 ]
Duchene, Jacques [1 ]
机构：
[1] Univ Technol Troyes, ICD, FRE 2848, CNRS,Lab Modelisat & Surete Syst LM2S, F-10010 Troyes, France
来源：
NDS: 2009 INTERNATIONAL WORKSHOP ON MULTIDIMENSIONAL (ND) SYSTEMS | 2009年
关键词：
HILBERT SPECTRUM; TIME-SERIES;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
In this work, an Empirical Mode Decomposition (EMD) of bivariate signals is proposed. It permits to decompose signals into elementary rotating functions, oscillating functions and tendencies. The technique is based on recursive extraction of non planar and rapidly rotating functions, and then a recursive extraction of rapidly oscillating functions as in case of univariate EMD. Our concept is based on a theoretical decomposition and is confirmed on simulated signals.
引用
收藏
页码：91 / 94
页数：4
相关论文
共 50 条
  • [1] Thermal Image Filtering by Bi-dimensional Empirical Mode Decomposition
    Mihai-Bogdan, Gavriloaia
    Constantin-Radu, Vizireanu
    Octavian, Fratu
    Constantin, Mara
    Dragos-Nicolae, Vizireanu
    Radu, Preda
    Gheorghe, Gavriloaia
    [J]. ADVANCED TOPICS IN OPTOELECTRONICS, MICROELECTRONICS, AND NANOTECHNOLOGIES VII, 2015, 9258
  • [2] A Bi-Dimensional Empirical Mode Decomposition Based Watermarking Scheme
    Amira-Biad, Souad
    Bouden, Toufik
    Nibouche, Mokhtar
    Elbasi, Ersin
    [J]. INTERNATIONAL ARAB JOURNAL OF INFORMATION TECHNOLOGY, 2015, 12 (01) : 24 - 31
  • [3] Robust Watermarking Algorithm Based on Bi-dimensional Empirical Mode Decomposition
    Deng, Minghui
    Yang, Fang
    Wang, Runtao
    [J]. ADVANCED RESEARCH ON INDUSTRY, INFORMATION SYSTEMS AND MATERIAL ENGINEERING, PTS 1-7, 2011, 204-210 : 627 - 631
  • [4] Gradient Constrained Bi-dimensional Empirical Mode Decomposition and Its Application
    Xu, Xiaogang
    Chong, Yuan
    Jin, Xin
    Wang, Jianguo
    Xu, Guanlei
    Qin, Xujia
    [J]. 2015 8TH INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING (CISP), 2015, : 929 - 933
  • [5] Improved bi-dimensional empirical mode decomposition based on 2D-assisted signals: analysis and application
    Xu, G. L.
    Wang, X. T.
    Xu, X. G.
    [J]. IET IMAGE PROCESSING, 2011, 5 (03) : 205 - 221
  • [6] Iteration-Free Bi-Dimensional Empirical Mode Decomposition and Its Application
    Titijaroonroj, Taravichet
    Woraratpanya, Kuntpong
    [J]. IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, 2017, E100D (09): : 2183 - 2196
  • [7] Pansharpening Scheme Using Bi-dimensional Empirical Mode Decomposition and Neural Network
    Saxena, Nidhi
    Raman, Balasubramanian
    [J]. ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS, 2022, 18 (04)
  • [8] A green's function-based Bi-dimensional empirical mode decomposition
    Al-Baddai, Saad
    Al-Subari, Karema
    Tome, Ana Maria
    Sole-Casals, Jordi
    Lang, Elmar Wolfgang
    [J]. INFORMATION SCIENCES, 2016, 348 : 305 - 321
  • [9] Hierarchical Order Statistics Filtering for Fast Bi-Dimensional Empirical Mode Decomposition
    Semiz, Serkan
    Celebi, Anil
    Urhan, Oguzhan
    [J]. ETRI JOURNAL, 2016, 38 (04) : 695 - 702
  • [10] Automatic Detection of Masses in Mammograms Using Bi-Dimensional Empirical Mode Decomposition
    Vaijayanthi, N.
    Caroline, B. Elizabeth
    Murugan, V. Senthilvel
    [J]. JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS, 2018, 8 (07) : 1326 - 1341
12345