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Journal of Inverse and Ill-posed Problems

Editor-in-Chief: Kabanikhin, Sergey I.

6 Issues per year


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1569-3945
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Volume 15, Issue 3

Issues

Regularization by dynamic programming

S. Kindermann
  • Radon Institute for Computational and Applied Mathematics, Austrian Academy of Sciences, Altenbergerstrasse 69, A-4040 Linz, Austria. Email:
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/ A. Leitão
  • Department of Mathematics, Federal University of St. Catarina, P.O. Box 476, 88.040-900 Florianopolis, Brazil. Email:
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Published Online: 2007-06-25 | DOI: https://doi.org/10.1515/jiip.2007.016

We investigate continuous regularization methods for linear inverse problems of static and dynamic type. These methods are based on dynamic programming approaches for linear quadratic optimal control problems. We prove regularization properties and also obtain rates of convergence for our methods. A numerical example concerning a dynamical electrical impedance tomography (EIT) problem is used to illustrate the theoretical results.

Key Words: Regularization,; dynamic programming,; inverse problems,; Hamilton–Jacobi equation,; electrical impedance tomography,; dynamic inverse problems.

About the article

Published Online: 2007-06-25

Published in Print: 2007-06-19


Citation Information: Journal of Inverse and Ill-posed Problems jiip, Volume 15, Issue 3, Pages 295–310, ISSN (Online) 1569-3953, ISSN (Print) 0928-0219, DOI: https://doi.org/10.1515/jiip.2007.016.

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B Kaltenbacher
Inverse Problems, 2017, Volume 33, Number 6, Page 064002
[2]
B N Hahn
Inverse Problems, 2014, Volume 30, Number 3, Page 035008

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