Approximate Global Convergence and Adaptivity for Coefficient Inverse Problems

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...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριοι συγγραφείς: Beilina, Larisa (Συγγραφέας), Klibanov, Michael Victor (Συγγραφέας)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Boston, MA : Springer US, 2012.
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
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100 1 |a Beilina, Larisa.  |e author. 
245 1 0 |a Approximate Global Convergence and Adaptivity for Coefficient Inverse Problems  |h [electronic resource] /  |c by Larisa Beilina, Michael Victor Klibanov. 
264 1 |a Boston, MA :  |b Springer US,  |c 2012. 
300 |a XVI, 408 p.  |b online resource. 
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505 0 |a Two Central Questions of This Book and an Introduction to the Theories of Ill-Posed and Coefficient Inverse Problems -- Approximately Globally Convergent Numerical Method -- Numerical Implementation of the Approximately Globally Convergent Method -- The Adaptive Finite Element Technique and its Synthesis with the Approximately Globally Convergent Numerical Method -- Blind Experimental Data -- Backscattering Data. 
520 |a 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 approximation 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. 
650 0 |a Mathematics. 
650 0 |a Global analysis (Mathematics). 
650 0 |a Manifolds (Mathematics). 
650 0 |a Partial differential equations. 
650 0 |a Numerical analysis. 
650 0 |a Physics. 
650 0 |a Applied mathematics. 
650 0 |a Engineering mathematics. 
650 1 4 |a Mathematics. 
650 2 4 |a Partial Differential Equations. 
650 2 4 |a Numerical and Computational Physics. 
650 2 4 |a Appl.Mathematics/Computational Methods of Engineering. 
650 2 4 |a Numerical Analysis. 
650 2 4 |a Global Analysis and Analysis on Manifolds. 
700 1 |a Klibanov, Michael Victor.  |e author. 
710 2 |a SpringerLink (Online service) 
773 0 |t Springer eBooks 
776 0 8 |i Printed edition:  |z 9781441978042 
856 4 0 |u http://dx.doi.org/10.1007/978-1-4419-7805-9  |z Full Text via HEAL-Link 
912 |a ZDB-2-SMA 
950 |a Mathematics and Statistics (Springer-11649)