期刊
COMPUTATIONAL OPTIMIZATION AND APPLICATIONS
卷 81, 期 2, 页码 569-611出版社
SPRINGER
DOI: 10.1007/s10589-021-00343-x
关键词
Inverse problems; Iterative regularization; Coefficient identification in elliptic PDEs; Impedance acoustic tomography
资金
- University of Klagenfurt
In this paper, we study the formulation of inverse problems as constrained minimization problems and their iterative solution by gradient or Newton type methods. We carry out a convergence analysis in the sense of regularization methods and discuss applicability to the problem of identifying the spatially varying diffusivity in an elliptic PDE from different sets of observations. Among these is a novel hybrid imaging technology known as impedance acoustic tomography, for which we provide numerical experiments.
In this paper we study the formulation of inverse problems as constrained minimization problems and their iterative solution by gradient or Newton type methods. We carry out a convergence analysis in the sense of regularization methods and discuss applicability to the problem of identifying the spatially varying diffusivity in an elliptic PDE from different sets of observations. Among these is a novel hybrid imaging technology known as impedance acoustic tomography, for which we provide numerical experiments.
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