A Novel Gaussian Window Approach for Empirical Mode Decomposition

摘要：

Empirical mode decomposition (EMD) is an algorithmic construction for decomposing multi-component signals into a series of intrinsic mode functions (IMFs). However, traditional EMD may encounter the difficulty of mode mixing when a signal contains intermittency. To solve the difficulty, a Gaussian window averaging method is proposed to construct the mean envelope of a given signal in each sifting process. The numerical analysis also demonstrates promising reliability with the proposed algorithm.

关键词： Empirical mode decomposition Intrinsic mode function Mode mixing Gaussian

作者: Shuen De Wu Chiu-Wen Wu Cha-Lin Liu Yan-Hao Huang Kung-Yen Lee

作者单位: Department of Mechatronic Technology, National Taiwan Normal University, Taipei, Taiwan Department of multimedia and Animation Art, National Taiwan University of Arts, Taipei, Taiwan Department of Engineering Science and Ocean Engineering, National Taiwan University, Taipei,Taiwan Department of Engineering Science and Ocean Engineering, National Taiwan University, Taipei, Taiwan

会议类型: 国际会议

会议名称: 2011 International Conference on Advanced Materials and Engineering Materials(2011先进材料与工程材料国际会议 ICAMEM 2011)

会议地点: 沈阳

会议语种:英文

页码: 274-277

在线出版日期: 2011-11-22（万方平台首次上网日期，不代表论文的发表时间）