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Journal of Inverse and Ill-posed Problems

Editor-in-Chief: Kabanikhin, Sergey I.

6 Issues per year


IMPACT FACTOR increased in 2014: 0.880
Rank 74 out of 310 in category Mathematics and 113 out of 255 in Applied Mathematics in the 2014 Thomson Reuters Journal Citation Report/Science Edition

SCImago Journal Rank (SJR) 2014: 0.516
Source Normalized Impact per Paper (SNIP) 2014: 1.430
Impact per Publication (IPP) 2014: 0.613

Mathematical Citation Quotient (MCQ) 2014: 0.51

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Regularization by dynamic programming

S. Kindermann1 / A. Leitão2

1Radon Institute for Computational and Applied Mathematics, Austrian Academy of Sciences, Altenbergerstrasse 69, A-4040 Linz, Austria. Email:

2Department of Mathematics, Federal University of St. Catarina, P.O. Box 476, 88.040-900 Florianopolis, Brazil. Email:

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: 10.1515/jiip.2007.016, June 2007

Publication History

Published Online:
2007-06-25

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.

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[1]
B N Hahn
Inverse Problems, 2014, Volume 30, Number 3, Page 035008

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