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Variational regularization for syste...

Huber, Richard.

Variational regularization for systems of inverse problemsTikhonov regularization with multiple forward operators /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Variational regularization for systems of inverse problemsby Richard Huber.
Reminder of title:	Tikhonov regularization with multiple forward operators /
Author:	Huber, Richard.
Published:	Wiesbaden :Springer Fachmedien Wiesbaden :2019.
Description:	ix, 136 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Inverse problems (Differential equations)
Online resource:	https://doi.org/10.1007/978-3-658-25390-5
ISBN:	9783658253905$q(electronic bk.)

Variational regularization for systems of inverse problemsTikhonov regularization with multiple forward operators /
Huber, Richard.

Variational regularization for systems of inverse problemsTikhonov regularization with multiple forward operators /[electronic resource] :by Richard Huber. - Wiesbaden :Springer Fachmedien Wiesbaden :2019. - ix, 136 p. :ill., digital ;24 cm. - BestMasters,2625-3577. - BestMasters..

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.

ISBN: 9783658253905$q(electronic bk.)

Standard No.: 10.1007/978-3-658-25390-5doiSubjects--Topical Terms:

189581
Inverse problems (Differential equations)

LC Class. No.: QA371

Dewey Class. No.: 515.357

Variational regularization for systems of inverse problemsTikhonov regularization with multiple forward operators /
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520 $a 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.
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