Solution of the inverse scattering problem from inhomogeneous media using affine invariant sampling

被引：2
|
作者：
Daza, Maria L. [1 ]
Capistran, Marcos A. [1 ]
Andres Christen, J. [1 ]
Guadarrama, Lili [2 ]
机构：
[1] Ctr Invest Matemat AC, Jalisco S-N, Guanajuato 36240, Gto, Mexico
[2] Ctr Invest Matemat AC, Unidad Aguascalientes, F Bartolome de las Casas 314, Aguascalientes 20259, Ags, Mexico
来源：
MATHEMATICAL METHODS IN THE APPLIED SCIENCES | 2017年 / 40卷 / 09期
关键词：
scattering; Bayesian inference; near-field; MCMC; affine invariant; UNCERTAINTY QUANTIFICATION; ALGORITHM;
D O I：
10.1002/mma.3929
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
We pose a Bayesian formulation of the inverse problem associated to recovering both the support and the refractive index of a convex obstacle given measurements of near-field scattered waves. Aiming at sampling efficiently from the arising posterior distribution usingMarkov Chain Monte Carlo, we construct a sampler (probability transition kernel) that is invariant under affine transformations of space. A point cloud method is used to approximate the scatterer support. We show that affine invariant sampling can successfully address the presence of multiple scales in inverse scattering in inhomogeneous media. Copyright (C) 2016 John Wiley & Sons, Ltd.
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页码：3311 / 3319
页数：9
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