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Model Misfit Minimization

文献类型：期刊论文

作者Fang, Yuanyuan1,2,3; Zhou, Ying1; Yao, Zhenxing2,3
刊名BULLETIN OF THE SEISMOLOGICAL SOCIETY OF AMERICA
出版日期2019-10-01
卷号109期号:5页码:1729-1737
ISSN号0037-1106
DOI10.1785/0120190079
英文摘要In geophysical applications, solutions to ill-posed inverse problems Ax = b are often obtained by analyzing the trade-off between data residue parallel to Ax - b parallel to(2) and model norm parallel to x parallel to(2). In this study, we show that the traditional L-curve analysis does not lead to solutions closest to the true models because the maximum curvature (or the corner of the L-curve) depends on the relative scaling between data residue and model norm. A Bayes approach based on empirical risk function minimization using training datasets may be designed to find a statistically optimal solution, but its success depends on the true realization of the model. To overcome this limitation, we construct training models using eigenvectors of matrix A(T)A as well as spectral coefficients calculated from the correlation between observations and eigenvector projected data. This approach accounts for data noise level but does not require it as a priori knowledge. Using global tomography as an example, we show that the solutions are closest to true models.
WOS关键词UPPER-MANTLE ; WAVE ; INVERSION ; REGULARIZATION ; SCATTERING ; TIME
资助项目National Natural Science Foundation of China[41630210] ; National Natural Science Foundation of China[41374047] ; U.S. National Science Foundation[EAR-1737737] ; Advanced Research Computing at Virginia Tech
WOS研究方向Geochemistry & Geophysics
语种英语
出版者SEISMOLOGICAL SOC AMER
WOS记录号WOS:000487813300012
资助机构National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; U.S. National Science Foundation ; U.S. National Science Foundation ; U.S. National Science Foundation ; U.S. National Science Foundation ; Advanced Research Computing at Virginia Tech ; Advanced Research Computing at Virginia Tech ; Advanced Research Computing at Virginia Tech ; Advanced Research Computing at Virginia Tech ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; U.S. National Science Foundation ; U.S. National Science Foundation ; U.S. National Science Foundation ; U.S. National Science Foundation ; Advanced Research Computing at Virginia Tech ; Advanced Research Computing at Virginia Tech ; Advanced Research Computing at Virginia Tech ; Advanced Research Computing at Virginia Tech ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; U.S. National Science Foundation ; U.S. National Science Foundation ; U.S. National Science Foundation ; U.S. National Science Foundation ; Advanced Research Computing at Virginia Tech ; Advanced Research Computing at Virginia Tech ; Advanced Research Computing at Virginia Tech ; Advanced Research Computing at Virginia Tech ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; U.S. National Science Foundation ; U.S. National Science Foundation ; U.S. National Science Foundation ; U.S. National Science Foundation ; Advanced Research Computing at Virginia Tech ; Advanced Research Computing at Virginia Tech ; Advanced Research Computing at Virginia Tech ; Advanced Research Computing at Virginia Tech
源URL[http://ir.iggcas.ac.cn/handle/132A11/93712]  
专题地质与地球物理研究所_中国科学院地球与行星物理重点实验室
通讯作者Zhou, Ying
作者单位1.Virginia Tech, Dept Geosci, Blacksburg, VA 24061 USA
2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
3.Chinese Acad Sci, Inst Geol & Geophys, Key Lab Earth & Planetary Phys, Beijing 100029, Peoples R China
推荐引用方式
GB/T 7714		 Fang, Yuanyuan,Zhou, Ying,Yao, Zhenxing. Model Misfit Minimization[J]. BULLETIN OF THE SEISMOLOGICAL SOCIETY OF AMERICA,2019,109(5):1729-1737.
APA Fang, Yuanyuan,Zhou, Ying,&Yao, Zhenxing.(2019).Model Misfit Minimization.BULLETIN OF THE SEISMOLOGICAL SOCIETY OF AMERICA,109(5),1729-1737.
MLA Fang, Yuanyuan,et al."Model Misfit Minimization".BULLETIN OF THE SEISMOLOGICAL SOCIETY OF AMERICA 109.5(2019):1729-1737.

入库方式： OAI收割

来源：地质与地球物理研究所

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