On regularization methods for inverse problems of dynamic type
Numerical Analysis
2021-01-26 v1 Numerical Analysis
Abstract
In this paper we consider new regularization methods for linear inverse problems of dynamic type. These methods are based on dynamic programming techniques for linear quadratic optimal control problems. Two different approaches are followed: a continuous and a discrete one. We prove regularization properties and also obtain rates of convergence for the methods derived from both approaches. A numerical example concerning the dynamic EIT problem is used to illustrate the theoretical results.
Cite
@article{arxiv.2101.09327,
title = {On regularization methods for inverse problems of dynamic type},
author = {S. Kindermann and A. Leitao},
journal= {arXiv preprint arXiv:2101.09327},
year = {2021}
}
Comments
24 pages, 3 figures