Empirical mode decomposition algorithm for bioradar data analysis

L. Anishchenko
{"title":"Empirical mode decomposition algorithm for bioradar data analysis","authors":"L. Anishchenko","doi":"10.1109/COMCAS.2015.7360429","DOIUrl":null,"url":null,"abstract":"In present work we discuss the usage of empirical mode decomposition algorithm for bioradar data processing. The algorithm of data processing is considered and the value of the threshold criteria is chosen according to the results of the experimental data processing. It is shown that preprocessing of raw bioradar data, which compensate the difference in amplitude of breathing and heartbeat signals, increases the effectiveness of empirical mode decomposition algorithm in bioradar data processing.","PeriodicalId":431569,"journal":{"name":"2015 IEEE International Conference on Microwaves, Communications, Antennas and Electronic Systems (COMCAS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE International Conference on Microwaves, Communications, Antennas and Electronic Systems (COMCAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/COMCAS.2015.7360429","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

Abstract

In present work we discuss the usage of empirical mode decomposition algorithm for bioradar data processing. The algorithm of data processing is considered and the value of the threshold criteria is chosen according to the results of the experimental data processing. It is shown that preprocessing of raw bioradar data, which compensate the difference in amplitude of breathing and heartbeat signals, increases the effectiveness of empirical mode decomposition algorithm in bioradar data processing.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
生物雷达数据分析的经验模态分解算法
在本工作中,我们讨论了经验模式分解算法在生物雷达数据处理中的应用。考虑了数据处理的算法,并根据实验数据处理结果选择了阈值准则的取值。实验结果表明,生物雷达原始数据的预处理补偿了呼吸和心跳信号的幅值差异,提高了经验模态分解算法在生物雷达数据处理中的有效性。
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 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Back-projected cortical potential imaging for monitoring and stimulation tools An industry-level implementation of a compact microwave diode switch matrix for flexible input multiplexing if a geo-stationary satellite payload Microwave imaging and microwave induced thermoacoustic tomography Observability conditions for fusion of asynchronous measurements from multiple passive sensors A 300 GHz multi-stage balanced variable gain amplifier with Tandem-X couplers
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1