Convergence Analysis of Asymptotical Regularization and Runge-Kutta Integrators for Linear Inverse Problems under Variational Source Conditions

Convergence Analysis of Asymptotical Regularization and Runge-Kutta Integrators for Linear Inverse Problems under Variational Source Conditions

Year:    2020

Author:    Yubin Zhao, Peter Mathé, Shuai Lu

CSIAM Transactions on Applied Mathematics, Vol. 1 (2020), Iss. 4 : pp. 693–714

Abstract

Variational source conditions are known to be a versatile tool for establishing error bounds, and these recently attract much attention. We establish sufficient conditions for general spectral regularization methods which yield convergence rates under variational source conditions. Specifically, we revisit the asymptotical regularization, Runge-Kutta integrators, and verify that these methods satisfy the proposed conditions. Numerical examples confirm the theoretical findings.

You do not have full access to this article.

Already a Subscriber? Sign in as an individual or via your institution

Journal Article Details

Publisher Name:    Global Science Press

Language:    English

DOI:    https://doi.org/10.4208/csiam-am.2020-0022

CSIAM Transactions on Applied Mathematics, Vol. 1 (2020), Iss. 4 : pp. 693–714

Published online:    2020-01

AMS Subject Headings:    Global Science Press

Copyright:    COPYRIGHT: © Global Science Press

Pages:    22

Keywords:    Linear ill-posed problems regularization theory variational source conditions asymptotical regularization Runge-Kutta integrators.

Author Details

Yubin Zhao

Peter Mathé

Shuai Lu