The linear sampling method for inhomogeneous medium and buried objects from far field measurements
Qin, Haihua1; Liu, Xiaodong2
刊名APPLIED NUMERICAL MATHEMATICS
2016-07-01
卷号105页码:82-95
关键词Inverse acoustic scattering Linear sampling method Mixed reciprocity principle Inhomogeneous background Buried object
ISSN号0168-9274
DOI10.1016/j.apnum.2015.11.006
英文摘要We are concerned with the reconstruction of both the penetrable inhomogeneous medium and the buried impenetrable obstacle. Firstly, the classical linear sampling method is used to recover the support of the inhomogeneous medium, and then a modification of the linear sampling method is proposed for objects buried in a known layered medium. The main feature of our method is that it avoids using knowledge of the Green's function for the background media. Finally, some numerical experiments are presented to demonstrate the feasibility and effectiveness of our method. (C) 2016 IMACS. Published by Elsevier B.V. All rights reserved.
资助项目NNSF of China[11501562] ; NNSF of China[11571355] ; Fundamental Research Funds for the Central Universities[2015QNA49] ; National Center for Mathematics and Interdisciplinary Sciences, CAS
WOS研究方向Mathematics
语种英语
出版者ELSEVIER SCIENCE BV
WOS记录号WOS:000375813300005
内容类型期刊论文
源URL[http://ir.amss.ac.cn/handle/2S8OKBNM/22633]  
专题应用数学研究所
通讯作者Liu, Xiaodong
作者单位1.China Univ Min & Technol, Dept Math, Xuzhou 221116, Jiangsu, Peoples R China
2.Chinese Acad Sci, Inst Appl Math, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714
Qin, Haihua,Liu, Xiaodong. The linear sampling method for inhomogeneous medium and buried objects from far field measurements[J]. APPLIED NUMERICAL MATHEMATICS,2016,105:82-95.
APA Qin, Haihua,&Liu, Xiaodong.(2016).The linear sampling method for inhomogeneous medium and buried objects from far field measurements.APPLIED NUMERICAL MATHEMATICS,105,82-95.
MLA Qin, Haihua,et al."The linear sampling method for inhomogeneous medium and buried objects from far field measurements".APPLIED NUMERICAL MATHEMATICS 105(2016):82-95.
个性服务
查看访问统计
相关权益政策
暂无数据
收藏/分享
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。


©版权所有 ©2017 CSpace - Powered by CSpace