2018
DOI: 10.1080/01630563.2018.1432645
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Noniterative Reconstruction Method for an Inverse Potential Problem Modeled by a Modified Helmholtz Equation

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Cited by 14 publications
(17 citation statements)
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“…with k, i ∈ R + , where i is the contrast with respect to the material property of the background k. Therefore, in comparison to Fernandez et al, 29,30 the main novelty of the current article is the consideration of a contrast on the material properties in place of compact supported anomalies. This drives us to choose completely different adjoint and auxiliary states whose analysis led us to use the Bessel's functions of different types.…”
Section: Introductionmentioning
confidence: 96%
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“…with k, i ∈ R + , where i is the contrast with respect to the material property of the background k. Therefore, in comparison to Fernandez et al, 29,30 the main novelty of the current article is the consideration of a contrast on the material properties in place of compact supported anomalies. This drives us to choose completely different adjoint and auxiliary states whose analysis led us to use the Bessel's functions of different types.…”
Section: Introductionmentioning
confidence: 96%
“…Following the original ideas presented in Fernandez et al,() in this paper, we are interested in the open problem,, pp126, problem 4.2 whose physical motivation comes out from semiconductors theory. See also the book of Isakov .…”
Section: Introductionmentioning
confidence: 99%
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“…We consider an inverse geometric problem for the modified Helmholtz equation to determine unknown obstacles from a single pair of boundary Cauchy data on an exterior surface . Over the past few decades, there has been extensive studies in numerical methods for the modified Helmholtz equation (Fernandez et al 2018(Fernandez et al , 2019Hua et al 2017), which arises in many important fields of physics and engineering (Lesnic and Bin-Mohsin 2012;Liang and Subramaniam 1997;Callihan and Wood 2012;Bakker and Kuhlman 2011;Politis et al 2002). In this paper, what we are interested in using reconstruction algorithms to detect the salient features of unknown obstacles within a body.…”
Section: Introductionmentioning
confidence: 99%