@Article{CAM-19-24,
author = {},
title = {【期刊信息】Inverse Problems and Imaging (IPI), Volume 16, Issue 6, December 2022},
journal = {CAM-Net Digest},
year = {2022},
volume = {19},
number = {24},
pages = {8--8},
abstract = {<p style="text-align: justify;">URL:&nbsp;<a href="https://www.aimsciences.org/ipi/article/2022/16/6">https://www.aimsciences.org/ipi/article/2022/16/6</a></p><p style="text-align: justify;">Special issue on analytical aspects of inverse problems in PDEs</p><p style="text-align: justify;">Preface<br/>Katya Krupchyk, Mikko Salo, Gunther Uhlmann and Jenn-Nan Wang</p><p style="text-align: justify;">On the scientific work of Victor Isakov<br/>Katya Krupchyk, Mikko Salo, Gunther Uhlmann and Jenn-Nan Wang</p><p style="text-align: justify;">New notions and constructions of the boundary control method<br/>M. I. Belishev</p><p style="text-align: justify;">A spectral target signature for thin surfaces with higher order jump conditions<br/>Fioralba Cakoni, Heejin Lee, Peter Monk and Yangwen Zhang</p><p style="text-align: justify;">Two single-measurement uniqueness results for inverse scattering problems within polyhedral geometries<br/>Xinlin Cao, Huaian Diao, Hongyu Liu and Jun Zou</p><p style="text-align: justify;">Global unique continuation from the boundary for a system of viscoelasticity with analytic coefficients and a memory term<br/>Matthias Eller, Naofumi Honda, Ching-Lung Lin and Gen Nakamura</p><p style="text-align: justify;">Microlocal analysis of borehole seismic data<br/>Raluca Felea, Romina Gaburro, Allan Greenleaf and Clifford Nolan</p><p style="text-align: justify;">A uniqueness theorem for inverse problems in quasilinear anisotropic media<br/>Md. Ibrahim Kholil and Ziqi Sun</p><p style="text-align: justify;">Convexification-based globally convergent numerical method for a 1D coefficient inverse problem with experimental data<br/>Michael V. Klibanov, Thuy T. Le, Loc H. Nguyen, Anders Sullivan and Lam Nguyen</p><p style="text-align: justify;">Refined instability estimates for some inverse problems<br/>Pu-Zhao Kow and Jenn-Nan Wang</p><p style="text-align: justify;">Kantorovich-Rubinstein metric based level-set methods for inverting modulus of gravity-force data<br/>Wenbin Li and Jianliang Qian</p><p style="text-align: justify;">Linearized inverse Schrödinger potential problem with partial data and its deep neural network inversion<br/>Sen Zou, Shuai Lu and Boxi Xu</p>},
issn = {},
doi = {https://doi.org/2022-CAM-21287},
url = {https://global-sci.com/article/75015/inverse-problems-and-imaging-ipi-volume-16-issue-6-december-2022}
}