Regularization of Inverse Problems, Heinz Werner Engl; Martin Hanke; A. Neubauer

Автор: Adrian Doicu; Thomas Trautmann; Franz Schreier
Название: Numerical Regularization for Atmospheric Inverse Problems
ISBN: 3642424015 ISBN-13(EAN): 9783642424014
Издательство: Springer
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Цена: 26120.00 р.
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Описание: Written by brilliant mathematicians, this research monograph presents and analyzes numerical algorithms for atmospheric retrieval, pulling together all the relevant material in a consistent, very powerful manner.

Автор: Michel Thera; Rainer Tichatschke
Название: Ill-posed Variational Problems and Regularization Techniques
ISBN: 3540663231 ISBN-13(EAN): 9783540663232
Издательство: Springer
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Цена: 15372.00 р.
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Описание: Developments in the field of ill-posed variational problems and variational inequalities are presented here. The work covers a large range of theoretical, numerical and practical aspects.

Автор: S.F. Gilyazov; N.L. Gol`dman
Название: Regularization of Ill-Posed Problems by Iteration Methods
ISBN: 0792361318 ISBN-13(EAN): 9780792361312
Издательство: Springer
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Цена: 15372.00 р.
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Описание: Iteration regularization, i.e., utilization of iteration methods of any form for the stable approximate solution of ill-posed problems, is one of the most important but still insufficiently developed topics of the new theory of ill-posed problems.

Автор: S.F. Gilyazov; N.L. Gol`dman
Название: Regularization of Ill-Posed Problems by Iteration Methods
ISBN: 9048153824 ISBN-13(EAN): 9789048153824
Издательство: Springer
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Цена: 13974.00 р.
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Описание: Iteration regularization, i.e., utilization of iteration methods of any form for the stable approximate solution of ill-posed problems, is one of the most important but still insufficiently developed topics of the new theory of ill-posed problems.

Автор: Eric Gautier and Pierre Alquier
Название: Inverse problems and high-dimensional estimation
ISBN: 3642199887 ISBN-13(EAN): 9783642199882
Издательство: Springer
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Цена: 15372.00 р.
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Описание: The product of a high-flying summer school in Paris in 2009, this volume synthesises the state of the art on ill-posed statistical inverse problems and high-dimensional estimation and explores the ways these techniques can be applied to economics.

Автор: Victor Isakov
Название: Inverse Problems for Partial Differential Equations
ISBN: 3319516574 ISBN-13(EAN): 9783319516578
Издательство: Springer
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Цена: 16769.00 р.
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Описание: By presenting the data in a readable and informative manner, the book introduces both scientific and engineering researchers as well as graduate students to the significant work done in this area in recent years, relating it to broader themes in mathematical analysis.

Автор: Llibre, Jaume Ramirez, Fellow In Strategy And Director Of The Oxford Scenarios Programme Rafael (department Of Management And Human Resources, Hec-par
Название: Inverse problems in ordinary differential equations and applications
ISBN: 3319263374 ISBN-13(EAN): 9783319263373
Издательство: Springer
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Цена: 13275.00 р.
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Описание: This book is dedicated to study the inverse problem of ordinary differential equations, that is it focuses in finding all ordinary differential equations that satisfy a given set of properties.

Автор: Kirsch, Andreas
Название: Introduction to the mathematical theory of inverse problems
ISBN: 1461428513 ISBN-13(EAN): 9781461428510
Издательство: Springer
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Цена: 11173.00 р.
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Описание: This book introduces the area of inverse problems. It examines basic notions and difficulties encountered with ill-posed problems and presents two special nonlinear inverse problems in detail: the inverse spectral problem and the inverse scattering problem.

Автор: Biegler
Название: Large-Scale Inverse Problems and Quantification of Uncertainty
ISBN: 0470697431 ISBN-13(EAN): 9780470697436
Издательство: Wiley
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Цена: 17733.00 р.
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Описание: This book focuses on computational methods for large-scale statistical inverse problems and provides an introduction to statistical Bayesian and frequentist methodologies. Recent research advances for approximation methods are discussed, along with Kalman filtering methods and optimization-based approaches to solving inverse problems.