000			03170nam a22005055i 4500
001			978-1-4419-7805-9
003			DE-He213
005			20140220083233.0
007			cr nn 008mamaa
008			120308s2012 xxu| s |||| 0|eng d
020			_a9781441978059 _9978-1-4419-7805-9
024	7		_a10.1007/978-1-4419-7805-9 _2doi
050		4	_aQA370-380
072		7	_aPBKJ _2bicssc
072		7	_aMAT007000 _2bisacsh
082	0	4	_a515.353 _223
100	1		_aBeilina, Larisa. _eauthor.
245	1	0	_aApproximate Global Convergence and Adaptivity for Coefficient Inverse Problems _h[electronic resource] / _cby Larisa Beilina, Michael Victor Klibanov.
264		1	_aBoston, MA : _bSpringer US, _c2012.
300			_aXV, 407p. 78 illus., 73 illus. in color. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
505	0		_aTwo 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			_aApproximate 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	_aMathematics.
650		0	_aGlobal analysis.
650		0	_aDifferential equations, partial.
650		0	_aNumerical analysis.
650		0	_aEngineering mathematics.
650	1	4	_aMathematics.
650	2	4	_aPartial Differential Equations.
650	2	4	_aNumerical and Computational Physics.
650	2	4	_aAppl.Mathematics/Computational Methods of Engineering.
650	2	4	_aNumerical Analysis.
650	2	4	_aGlobal Analysis and Analysis on Manifolds.
700	1		_aKlibanov, Michael Victor. _eauthor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9781441978042
856	4	0	_uhttp://dx.doi.org/10.1007/978-1-4419-7805-9
912			_aZDB-2-SMA
999			_c100543 _d100543