A conjugate-gradient-type rational Krylov subspace method for ill-posed problems-Reference-Cited by-同舟云学术

A conjugate-gradient-type rational Krylov subspace method for ill-posed problems

Published:2019-12-19 Issue:1 Volume:36 Page:015008
ISSN:0266-5611
Container-title:Inverse Problems
language:
Short-container-title:Inverse Problems

Author:

Grimm Volker^ORCID

Abstract

Abstract Conjugated gradients on the normal equation (CGNE) is a popular method to regularise linear inverse problems. The idea of the method can be summarised as minimising the residuum over a suitable Krylov subspace. It is shown that using the same idea for the shift-and-invert rational Krylov subspace yields an order-optimal regularisation scheme.

Funder

Deutsche Forschungsgemeinschaft

Publisher

IOP Publishing

Subject

Applied Mathematics,Computer Science Applications,Mathematical Physics,Signal Processing,Theoretical Computer Science

Link

https://iopscience.iop.org/article/10.1088/1361-6420/ab5819/pdf

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