计算机工程与应用 ›› 2010, Vol. 46 ›› Issue (4): 120-124.DOI: 10.3778/j.issn.1002-8331.2010.04.038

• 数据库、信号与信息处理 • 上一篇    下一篇

经验模式分解及其应用研究

王建国1,3,王孝通1,3,徐晓刚2,3   

  1. 1.海军大连舰艇学院 航海系,辽宁 大连 116018
    2.海军大连舰艇学院 装备系统与自动化系,辽宁 大连 116018
    3.海军大连舰艇学院 光电技术研究所,辽宁 大连 116018
  • 收稿日期:2009-02-05 修回日期:2009-03-20 出版日期:2010-02-01 发布日期:2010-02-01
  • 通讯作者: 王建国

Empirical Mode Decomposition and its application

WANG Jian-guo1,3,WANG Xiao-tong1,3,XU Xiao-gang2,3   

  1. 1.Department of Navigation,Dalian Naval Academy,Dalian,Liaoning 116018,China
    2.Department of Automatization,Dalian Naval Academy,Dalian,Liaoning 116018,China
    3.Institute of Photoelectric Technology,Dalian Naval Academy,Dalian,Liaoning 116018,China
  • Received:2009-02-05 Revised:2009-03-20 Online:2010-02-01 Published:2010-02-01
  • Contact: WANG Jian-guo

摘要: 经验模式分解(Empirical Mode Decomposition,EMD)是一种完全由数据驱动的自适应非线性时变信号分解方法,它将数据分解成具有物理意义的几个内蕴模式函数分量。介绍了一维EMD、二维EMD的基本概念、主要算法及其主要应用,指出了EMD的主要优点和缺点,给出了EMD研究与应用的发展趋势。

Abstract: Empirical Mode Decomposition(EMD) is a decomposition algorithm which is used to analyze nonlinear and time-varying signal.Different from the traditional signal analysis method,the decomposition is data-driven and self-adaptive.A review work about the current development of one dimensional EMD and bidimensional EMD is introduced.At first,some basic concepts,main algorithms and applications are described.Then the advantages and shortages of EMD are discussed.At the end of the paper,several problems which are waiting to be solved are listed.

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