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Hofmann, Bernd

New Trends in Parameter Identification for Mathematical Models

Hofmann, Bernd - New Trends in Parameter Identification for Mathematical Models, ebook

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ISBN: 9783319708249
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Table of contents

1. Posterior Contraction in Bayesian Inverse Problems Under Gaussian Priors
Sergios Agapiou, Peter Mathé

2. Convex Regularization of Discrete-Valued Inverse Problems
Christian Clason, Thi Bich Tram Do

3. Algebraic Reconstruction of Source and Attenuation in SPECT Using First Scattering Measurements
Evelyn Cueva, Axel Osses, Juan Carlos Quintana, Cristián Tejos, Matías Courdurier, Pablo Irarrazaval

4. On

1
-Regularization Under Continuity of the Forward Operator in Weaker Topologies
Daniel Gerth, Bernd Hofmann

5. On Self-regularization of Ill-Posed Problems in Banach Spaces by Projection Methods
Uno Hämarik, Urve Kangro

6. Monotonicity-Based Regularization for Phantom Experiment Data in Electrical Impedance Tomography
Bastian Harrach, Mach Nguyet Minh

7. An SVD in Spherical Surface Wave Tomography
Ralf Hielscher, Daniel Potts, Michael Quellmalz

8. Numerical Studies of Recovery Chances for a Simplified EIT Problem
Christopher Hofmann, Bernd Hofmann, Roman Unger

9. Bayesian Updating in the Determination of Forces in Euler-Bernoulli Beams
Alexandre Kawano, Abdelmalek Zine

10. On Nonstationary Iterated Tikhonov Methods for Ill-Posed Equations in Banach Spaces
M. P. Machado, F. Margotti, Antonio Leitão

11. The Product Midpoint Rule for Abel-Type Integral Equations of the First Kind with Perturbed Data
Robert Plato

12. Heuristic Parameter Choice in Tikhonov Method from Minimizers of the Quasi-Optimality Function
Toomas Raus, Uno Hämarik

13. Modification of Iterative Tikhonov Regularization Motivated by a Problem of Identification of Laser Beam Quality Parameters
Teresa Regińska, Kazimierz Regiński

14. Tomographic Terahertz Imaging Using Sequential Subspace Optimization
Anne Wald, Thomas Schuster

15. Adaptivity and Oracle Inequalities in Linear Statistical Inverse Problems: A (Numerical) Survey
Frank Werner

16. Relaxing Alternating Direction Method of Multipliers (ADMM) for Linear Inverse Problems
Zehui Wu, Shuai Lu

Keywords: Mathematics, Partial Differential Equations, Operator Theory, Calculus of Variations and Optimal Control; Optimization, Numerical Analysis

Editor
 
 
Publisher
Springer
Publication year
2018
Language
en
Edition
1
Series
Trends in Mathematics
Category
Natural Sciences
Format
Ebook
eISBN (PDF)
9783319708249
Printed ISBN
978-3-319-70823-2

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