Approximate Global Convergence and Adaptivity for Coefficient Inverse Problems

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Approximate Global Convergence and Adaptivity for Coefficient Inverse Problems is written by Larisa Beilina and published by Springer Science & Business Media. It's available with International Standard Book Number or ISBN identification 1441978054 (ISBN 10) and 9781441978059 (ISBN 13).

Approximate Global Convergence and Adaptivity for Coefficient Inverse Problems is the first book in which two new concepts of numerical solutions of multidimensional Coefficient Inverse Problems (CIPs) for a hyperbolic Partial Differential Equation (PDE) are presented: Approximate Global Convergence and the Adaptive Finite Element Method (adaptivity for brevity). Two central questions for CIPs are addressed: How to obtain a good approximations for the exact solution without any knowledge of a small neighborhood of this solution, and how to refine it given the approximation. The book also combines analytical convergence results with recipes for various numerical implementations of developed algorithms. The developed technique is applied to two types of blind experimental data, which are collected both in a laboratory and in the field. The result for the blind backscattering experimental data collected in the field addresses a real world problem of imaging of shallow explosives.