心电数据压缩的小波神经元选择方法

Xinping Yan, Qiaohui Guo, Yongming Yang
{"title":"心电数据压缩的小波神经元选择方法","authors":"Xinping Yan, Qiaohui Guo, Yongming Yang","doi":"10.1109/INDIN.2008.4618258","DOIUrl":null,"url":null,"abstract":"In this paper, a wavelet network for the Electrocardiograph (ECG) data compression and the selection of its wavelet neuron are presented. The methods of the frequency-domain matching and the orthogonal least square (OLS) algorithm in selecting the wavelet basis and its quantity were discussed. We choose Morlet wavelet as the mother wavelet, and use the ECG signal for simulation. The result demonstrates that the number of Morlet wavelets whose spectrums locating at the ECG is up to 152. But after filtrated by the OLS algorithm, it reduces sharply. This method can make the size of the wavelet network driving to optimum and reduce the training time of the wavelet network significantly. The algorithm also can reconstruct the ECG signal very well. The results of simulation indicate that it can reflect the location and intensity of all waves correctly. Consequently, the algorithm has higher compression ratio and fidelity.","PeriodicalId":112553,"journal":{"name":"2008 6th IEEE International Conference on Industrial Informatics","volume":"77 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Wavelet neuron selection method for ECG data compression\",\"authors\":\"Xinping Yan, Qiaohui Guo, Yongming Yang\",\"doi\":\"10.1109/INDIN.2008.4618258\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a wavelet network for the Electrocardiograph (ECG) data compression and the selection of its wavelet neuron are presented. The methods of the frequency-domain matching and the orthogonal least square (OLS) algorithm in selecting the wavelet basis and its quantity were discussed. We choose Morlet wavelet as the mother wavelet, and use the ECG signal for simulation. The result demonstrates that the number of Morlet wavelets whose spectrums locating at the ECG is up to 152. But after filtrated by the OLS algorithm, it reduces sharply. This method can make the size of the wavelet network driving to optimum and reduce the training time of the wavelet network significantly. The algorithm also can reconstruct the ECG signal very well. The results of simulation indicate that it can reflect the location and intensity of all waves correctly. Consequently, the algorithm has higher compression ratio and fidelity.\",\"PeriodicalId\":112553,\"journal\":{\"name\":\"2008 6th IEEE International Conference on Industrial Informatics\",\"volume\":\"77 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-07-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 6th IEEE International Conference on Industrial Informatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/INDIN.2008.4618258\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 6th IEEE International Conference on Industrial Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INDIN.2008.4618258","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

本文提出了一种用于心电数据压缩的小波网络及其小波神经元的选择。讨论了频域匹配和正交最小二乘(OLS)算法选择小波基及其数量的方法。我们选择Morlet小波作为母小波,用心电信号进行仿真。结果表明,在心电上定位的Morlet小波多达152个。但经过OLS算法的过滤后,它急剧减少。该方法可以使小波网络驱动的大小达到最优,并显著减少小波网络的训练时间。该算法还能很好地重建心电信号。仿真结果表明,该方法能较好地反映各波的位置和强度。因此,该算法具有较高的压缩比和保真度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
Wavelet neuron selection method for ECG data compression
In this paper, a wavelet network for the Electrocardiograph (ECG) data compression and the selection of its wavelet neuron are presented. The methods of the frequency-domain matching and the orthogonal least square (OLS) algorithm in selecting the wavelet basis and its quantity were discussed. We choose Morlet wavelet as the mother wavelet, and use the ECG signal for simulation. The result demonstrates that the number of Morlet wavelets whose spectrums locating at the ECG is up to 152. But after filtrated by the OLS algorithm, it reduces sharply. This method can make the size of the wavelet network driving to optimum and reduce the training time of the wavelet network significantly. The algorithm also can reconstruct the ECG signal very well. The results of simulation indicate that it can reflect the location and intensity of all waves correctly. Consequently, the algorithm has higher compression ratio and fidelity.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Safety supervision layer A feature selection method for Automated Visual Inspection systems Performances linkages between an airport and the Air Cargo Supply Chain — Evidences from Hong Kong and Singapore Kinematics control for a 6-DOF space manipulator based on ARM processor and FPGA Co-processor Remote robot control system based on DTMF of mobile phone
×
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