An Improved EMD Algorithm for Self-Adaptive Adjustment of Reference Point Position

Xilin Li, Dongxin Li
{"title":"An Improved EMD Algorithm for Self-Adaptive Adjustment of Reference Point Position","authors":"Xilin Li, Dongxin Li","doi":"10.1109/EEI59236.2023.10212642","DOIUrl":null,"url":null,"abstract":"Empirical Mode decomposition (EMD), invented by Huang et al., National Aeronautics and Space Administration (NASA), is an advanced signal processing method, which can effectively obtain the time-frequency characteristics of non-stationary signals. However, when the upper and lower envelope of the signal is used to construct the cubic spline curve to separate the signals of different modes, the signal distortion problems such as end effect will appear. On the basis of studying the existing methods of this problem, an adaptive method of extremum point position is proposed in this paper, which can reduce the distortion degree in the extraction process of different mode signals. The method takes full account of the intrinsic characteristics of signals, and the effect is better in a variety of evaluation criteria.","PeriodicalId":363603,"journal":{"name":"2023 5th International Conference on Electronic Engineering and Informatics (EEI)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 5th International Conference on Electronic Engineering and Informatics (EEI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EEI59236.2023.10212642","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Empirical Mode decomposition (EMD), invented by Huang et al., National Aeronautics and Space Administration (NASA), is an advanced signal processing method, which can effectively obtain the time-frequency characteristics of non-stationary signals. However, when the upper and lower envelope of the signal is used to construct the cubic spline curve to separate the signals of different modes, the signal distortion problems such as end effect will appear. On the basis of studying the existing methods of this problem, an adaptive method of extremum point position is proposed in this paper, which can reduce the distortion degree in the extraction process of different mode signals. The method takes full account of the intrinsic characteristics of signals, and the effect is better in a variety of evaluation criteria.
参考点位置自适应调整的改进EMD算法
经验模态分解(Empirical Mode decomposition, EMD)是由美国国家航空航天局(NASA) Huang等人发明的一种先进的信号处理方法,可以有效地获取非平稳信号的时频特性。然而,当利用信号的上下包络线构造三次样条曲线来分离不同模式的信号时,就会出现端点效应等信号畸变问题。本文在研究该问题现有方法的基础上,提出了一种自适应极值点位置方法,该方法可以降低不同模态信号提取过程中的失真程度。该方法充分考虑了信号的固有特性,在多种评价准则下效果较好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信