An entropic Landweber method for linear ill-posed problems
Optimization and Control
2020-01-29 v2 Numerical Analysis
Numerical Analysis
Abstract
The aim of this paper is to investigate the use of an entropic projection method for the iterative regularization of linear ill-posed problems. We derive a closed form solution for the iterates and analyze their convergence behaviour both in a case of reconstructing general nonnegative unknowns as well as for the sake of recovering probability distributions. Moreover, we discuss several variants of the algorithm and relations to other methods in the literature. The effectiveness of the approach is studied numerically in several examples.
Cite
@article{arxiv.1906.10032,
title = {An entropic Landweber method for linear ill-posed problems},
author = {Martin Burger and Elena Resmerita and Martin Benning},
journal= {arXiv preprint arXiv:1906.10032},
year = {2020}
}