Titlebook: Inverse Problems of Wave Propagation and Diffraction; Proceedings of the C Guy Chavent,Pierre C. Sabatier Conference proceedings 1997 Sprin

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书目名称Inverse Problems of Wave Propagation and Diffraction影响因子(影响力)




书目名称Inverse Problems of Wave Propagation and Diffraction影响因子(影响力)学科排名




书目名称Inverse Problems of Wave Propagation and Diffraction网络公开度




书目名称Inverse Problems of Wave Propagation and Diffraction网络公开度学科排名




书目名称Inverse Problems of Wave Propagation and Diffraction被引频次




书目名称Inverse Problems of Wave Propagation and Diffraction被引频次学科排名




书目名称Inverse Problems of Wave Propagation and Diffraction年度引用




书目名称Inverse Problems of Wave Propagation and Diffraction年度引用学科排名




书目名称Inverse Problems of Wave Propagation and Diffraction读者反馈




书目名称Inverse Problems of Wave Propagation and Diffraction读者反馈学科排名

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Conference proceedings 1997nterest are the contributions to two and three dimensional problems without reducing symmetries. Topics treated are the obstacle problem, scattering by classical media, and scattering by distributed media.

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Inverse scattering for N-body systems with time-dependent potentials,ttering operator with unperturbed evolution given by the free Hamiltonian. These results are obtained from reconstruction formulae with bound of the error term that I prove with a simple time-dependent method.

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Regularity of an inverse problem in wave propagation,n concerning regularity properties of the forward map is indispensable in the study of the inverse problem . smooth optimization methods. The usefulness of our results and some directions for future research are also discussed.

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Retrieval of object information from electron diffraction as Ill-posed inverse problems,s given by a generalized and regularized Moore-Penrose inverse. Extracting solely the atomic displacements the latter are given by the zeros of a function with an incompletely known Fourier spectrum. The numerical algorithms resulting from the fundamental relations imply ill-posed inverse problems.

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An overview of nonlinear diffraction tomography within the bayesian estimation framework,1), . (Chew and Wang 1990) and . (Kleinman and van den Berg 1992) — are interpreted as algorithms to compute the defined solution. This common point of view allows an objective comparison between these methods, from the standpoint of their convergence properties and the solution they provide.