scholarly journals A Bayesian level set method for geometric inverse problems

2016 ◽  
Vol 18 (2) ◽  
pp. 181-217 ◽  
Author(s):  
Marco Iglesias ◽  
Yulong Lu ◽  
Andrew Stuart
2001 ◽  
Vol 17 (5) ◽  
pp. 1327-1355 ◽  
Author(s):  
Martin Burger

2004 ◽  
Vol 20 (3) ◽  
pp. 673-696 ◽  
Author(s):  
Hend Ben Ameur ◽  
Martin Burger ◽  
Benjamin Hackl

2013 ◽  
Vol 2013 ◽  
pp. 1-15 ◽  
Author(s):  
A. De Cezaro

We investigate a level-set-type method for solving ill-posed problems, with the assumption that the solutions are piecewise, but not necessarily constant functions with unknown level sets and unknown level values. In order to get stable approximate solutions of the inverse problem, we propose a Tikhonov-type regularization approach coupled with a level-set framework. We prove the existence of generalized minimizers for the Tikhonov functional. Moreover, we prove convergence and stability for regularized solutions with respect to the noise level, characterizing the level-set approach as a regularization method for inverse problems. We also show the applicability of the proposed level-set method in some interesting inverse problems arising in elliptic PDE models.


Author(s):  
Luis Fernando Segalla ◽  
Alexandre Zabot ◽  
Diogo Nardelli Siebert ◽  
Fabiano Wolf

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