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＜E-Book＞
Variational Regularization for Systems of Inverse Problems : Tikhonov Regularization with Multiple Forward Operators / by Richard Huber
(BestMasters. ISSN:26253615)

Edition	1st ed. 2019.
Publisher	Wiesbaden : Springer Fachmedien Wiesbaden : Imprint: Springer Spektrum
Year	2019
Size	IX, 136 p. 1 illus : online resource
Authors	*Huber, Richard author SpringerLink (Online service)
Subjects	LCSH:Mathematics LCSH:Mathematical analysis LCSH:Mathematics—Data processing FREE:Applications of Mathematics FREE:Analysis FREE:Computational Mathematics and Numerical Analysis
Notes	General Tikhonov Regularization -- Specific Discrepancies -- Regularization Functionals -- Application to STEM Tomography Reconstruction Tikhonov regularization is a cornerstone technique in solving inverse problems with applications in countless scientific fields. Richard Huber discusses a multi-parameter Tikhonov approach for systems of inverse problems in order to take advantage of their specific structure. Such an approach allows to choose the regularization weights of each subproblem individually with respect to the corresponding noise levels and degrees of ill-posedness. Contents General Tikhonov Regularization Specific Discrepancies Regularization Functionals Application to STEM Tomography Reconstruction Target Groups Researchers and students in the field of mathematics Experts in the areas of mathematics, imaging, computer vision and nanotechnology The Author Richard Huber wrote his master’s thesis under the supervision of Prof. Dr. Kristian Bredies at the Institute for Mathematics and Scientific Computing at Graz University, Austria HTTP:URL=https://doi.org/10.1007/978-3-658-25390-5

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