Zobrazeno 1 - 10
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pro vyhledávání: '"Raik, Kemal"'
We investigate the transport of intensity equation (TIE) and the transport of phase equation (TPE) for solving the phase retrieval problem. Both the TIE and the TPE are derived from the paraxial Helmholtz equation and relate phase information to the
Externí odkaz:
http://arxiv.org/abs/2406.14143
The choice of a suitable regularization parameter is an important part of most regularization methods for inverse problems. In the absence of reliable estimates of the noise level, heuristic parameter choice rules can be used to accomplish this task.
Externí odkaz:
http://arxiv.org/abs/2205.09831
Autor:
Kindermann, Stefan, Raik, Kemal
Publikováno v:
Electronic Transactions on Numerical Analysis, Volume 53, pp. 217-238, 2020
The L-curve method is a well-known heuristic method for choosing the regularization parameter for ill-posed problems by selecting it according to the maximal curvature of the L-curve. In this article, we propose a simplified version that replaces the
Externí odkaz:
http://arxiv.org/abs/1908.10140
Autor:
Kindermann, Stefan, Raik, Kemal
Publikováno v:
SIAM J. Numer. Anal., 58(3), 1773-1800, 2020
We investigate the convergence theory of several known as well as new heuristic parameter choice rules for convex Tikhonov regularisation. The success of such methods is dependent on whether certain restrictions on the noise are satisfied. In the lin
Externí odkaz:
http://arxiv.org/abs/1905.06828
Autor:
Kindermann, Stefan, Raik, Kemal
Publikováno v:
Numerical Functional Analysis and Optimization, 40, 1373--1394, 2019
We study the choice of the regularisation parameter for linear ill-posed problems in the presence of noise that is possibly unbounded but only finite in a weaker norm, and when the noise-level is unknown. For this task, we analyse several heuristic p
Externí odkaz:
http://arxiv.org/abs/1809.06108
We study the choice of the regularisation parameter for linear ill-posed problems in the presence of data noise and operator perturbations, for which a bound on the operator error is known but the data noise-level is unknown. We introduce a new famil
Externí odkaz:
http://arxiv.org/abs/1807.05042
The choice of a suitable regularization parameter is an important part of most regularization methods for inverse problems. In the absence of reliable estimates of the noise level, heuristic parameter choice rules can be used to accomplish this task.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______386::91d3e26543776e3011b71af1f064055f
http://epub.oeaw.ac.at/?arp=buecher/Organisationseinheiten/_id105092_/ETNA/etna_Vol_57/pp216-241.pdf
http://epub.oeaw.ac.at/?arp=buecher/Organisationseinheiten/_id105092_/ETNA/etna_Vol_57/pp216-241.pdf
Autor:
Kindermann, Stefan1 (AUTHOR) kemal.raik@indmath.uni-linz.ac.at, Raik, Kemal1 (AUTHOR) kemal.raik@indmath.uni-linz.ac.at
Publikováno v:
Numerical Functional Analysis & Optimization. 2019, Vol. 40 Issue 12, p1373-1394. 22p.
A simplified L-curve method as error estimator. ETNA - Electronic Transactions on Numerical Analysis
Autor:
Raik, Kemal, Kindermann, Stefan
The L-curve method is a well known heuristic method for choosing the regularization parameter for ill-posed problems by selecting it according to the maximal curvature of the L-curve. In this article, we propose a simplified version that replaces the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______386::260f439a11f1a8816a3b1e77d89bbda2
http://epub.oeaw.ac.at/?arp=buecher/Organisationseinheiten/_id105092_/ETNA/etna_Vol_53/pp217-238.pdf
http://epub.oeaw.ac.at/?arp=buecher/Organisationseinheiten/_id105092_/ETNA/etna_Vol_53/pp217-238.pdf
Autor:
Raik, Kemal
In this thesis, we cover the so-called heuristic (aka error-free or data-driven) parameter choice rules for the regularisation of ill-posed problems (which just so happen to be prominent in the treatment of inverse problems). We consider the linear t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______3361::66300c2179bb770ee2d9762eeef86c4b