Runge-Kutta type total variation regularization for nonlinear inverse problems

Authors:
Li Li;Wanyu Liu
Affiliations:
-;-
Venue:
Journal of Computational and Applied Mathematics
Year:
2014

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Abstract

In this paper, we construct a Runge-Kutta type total variation regularization for the nonlinear ill-posed problems. This method resembles Runge-Kutta type iteration with the Bregman distance as a regularization functional. In the presence of noise with noise level @d we prove this method to be convergent under appropriate stopping rule. Furthermore, some numerical experiments are presented to verify this method to be more suitable for problems with discontinuous solutions.