电断层成像中直接和间接电导率分布图像重建算法的研究

M. Dorozhovets, Anton Prygrodsky
{"title":"电断层成像中直接和间接电导率分布图像重建算法的研究","authors":"M. Dorozhovets, Anton Prygrodsky","doi":"10.1109/IDAACS.2011.6072796","DOIUrl":null,"url":null,"abstract":"In this paper the two conductivity distribution reconstruction algorithms are presented. The first based on the previous resistivity reconstruction and the second one based on the usage of the inverse measured voltages. Efficiency of the presented algorithms compared with the direct conductivity distribution. Modeling results shows that these two algorithms provide better convergence of the iteration process of solving the inverse tomography problem.","PeriodicalId":106306,"journal":{"name":"Proceedings of the 6th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems","volume":"76 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Investigation of the direct and indirect conductivity distribution image reconstruction algorithms in electrical tomography\",\"authors\":\"M. Dorozhovets, Anton Prygrodsky\",\"doi\":\"10.1109/IDAACS.2011.6072796\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper the two conductivity distribution reconstruction algorithms are presented. The first based on the previous resistivity reconstruction and the second one based on the usage of the inverse measured voltages. Efficiency of the presented algorithms compared with the direct conductivity distribution. Modeling results shows that these two algorithms provide better convergence of the iteration process of solving the inverse tomography problem.\",\"PeriodicalId\":106306,\"journal\":{\"name\":\"Proceedings of the 6th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems\",\"volume\":\"76 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-11-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 6th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IDAACS.2011.6072796\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 6th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IDAACS.2011.6072796","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

本文给出了两种电导率分布重构算法。第一种方法是基于之前的电阻率重建,第二种方法是基于反测电压的使用。将所提算法与直接电导率分布进行了比较。建模结果表明,这两种算法在求解逆层析成像问题的迭代过程中具有较好的收敛性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Investigation of the direct and indirect conductivity distribution image reconstruction algorithms in electrical tomography
In this paper the two conductivity distribution reconstruction algorithms are presented. The first based on the previous resistivity reconstruction and the second one based on the usage of the inverse measured voltages. Efficiency of the presented algorithms compared with the direct conductivity distribution. Modeling results shows that these two algorithms provide better convergence of the iteration process of solving the inverse tomography problem.
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
×
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