Inverse Problems & Imaging
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Published By American Institute Of Mathematical Sciences

1930-8345

2021 ◽  
Vol 0 (0) ◽  
pp. 0
Author(s):  
Markus Harju ◽  
Jaakko Kultima ◽  
Valery Serov ◽  
Teemu Tyni

2021 ◽  
Vol 0 (0) ◽  
pp. 0
Author(s):  
Zhenwei Zhang ◽  
Xue Li ◽  
Yuping Duan ◽  
Ke Yin ◽  
Xue-Cheng Tai

2021 ◽  
Vol 0 (0) ◽  
pp. 0-0
Author(s):  
Xiaojuan Deng ◽  
◽  
Xing Zhao ◽  
Mengfei Li ◽  
Hongwei Li ◽  
...  

2021 ◽  
Vol 0 (0) ◽  
pp. 0-0
Author(s):  
Yuan Gao ◽  
◽  
Guangzhen Jin ◽  
Jian-Guo Liu ◽  
◽  
...  
Keyword(s):  

2021 ◽  
Vol 0 (0) ◽  
pp. 0-0
Author(s):  
Yiting Chen ◽  
◽  
Jia Li ◽  
Qingyun Yu

2021 ◽  
Vol 0 (0) ◽  
pp. 0
Author(s):  
Yuying Shi ◽  
Zijin Liu ◽  
Xiaoying Wang ◽  
Jinping Zhang

2021 ◽  
Vol 0 (0) ◽  
pp. 0
Author(s):  
Haigang Li ◽  
Jenn-Nan Wang ◽  
Ling Wang

<p style='text-indent:20px;'>In this paper we study the inverse problem of determining an electrical inclusion in a multi-layer composite from boundary measurements in 2D. We assume the conductivities in different layers are different and derive a stability estimate for the linearized map with explicit formulae on the conductivity and the thickness of each layer. Intuitively, if an inclusion is surrounded by a highly conductive layer, then, in view of "the principle of the least work", the current will take a path in the highly conductive layer and disregard the existence of the inclusion. Consequently, a worse stability of identifying the hidden inclusion is expected in this case. Our estimates indeed show that the ill-posedness of the problem increases as long as the conductivity of some layer becomes large. This work is an extension of the previous result by Nagayasu-Uhlmann-Wang[<xref ref-type="bibr" rid="b15">15</xref>], where a depth-dependent estimate is derived when an inclusion is deeply hidden in a conductor. Estimates in this work also show the influence of the depth of the inclusion.</p>


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