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一种用于逆体积散射问题的区域分解预处理方法。

A DOMAIN DECOMPOSITION PRECONDITIONING FOR AN INVERSE VOLUME SCATTERING PROBLEM.

作者信息

Borges Carlos, Biros George

机构信息

Department of Mathematics, University of Central Florida, Orlando, FL.

Department of Mechanical Engineering and Institute for Computation Engineering and Sciences, University of Texas, Austin, TX.

出版信息

Inverse Probl. 2020 Mar;36(3). doi: 10.1088/1361-6420/ab6e78. Epub 2020 Feb 14.

Abstract

We propose domain decomposition preconditioners for the solution of an integral equation formulation of the acoustic forward and inverse scattering problems. We study both forward and inverse volume problems and propose preconditioning techniques to accelerate the iterative solvers. For the forward scattering problem, we extend the domain decomposition based preconditioning techniques presented for partial differential equations in , to integral equations. We combine this domain decomposition preconditioner with a low-rank correction, which is easy to construct, forming a new preconditioner. For the inverse scattering problem, we use the forward problem preconditioner as a building block for constructing a preconditioner for the Gauss-Newton Hessian. We present numerical results that demonstrate the performance of both preconditioning strategies.

摘要

我们提出了用于求解声学正向和逆散射问题的积分方程公式的区域分解预条件器。我们研究了正向和逆体积问题,并提出了预条件技术以加速迭代求解器。对于正向散射问题,我们将文献中针对偏微分方程提出的基于区域分解的预条件技术扩展到积分方程。我们将这种区域分解预条件器与易于构造的低秩校正相结合,形成一个新的预条件器。对于逆散射问题,我们使用正向问题预条件器作为构建高斯 - 牛顿海森矩阵预条件器的基础模块。我们给出的数值结果展示了两种预条件策略的性能。

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3
Randomized algorithms for the low-rank approximation of matrices.
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