Regularisation by Krylov methods

Inverse problems are ubiquitous in many areas of Science and Engineering and, once discretised, they lead to ill-conditioned linear systems, often of huge dimensions: regularisation consists in replacing the original system by a nearby problem with better numerical properties, in order to find a meaningful approximation of its solution. After briefly surveying some standard regularisation methods, both iterative (such as many Krylov methods) and direct (such as Tikhonov method), this talk will introduce the recent class of the Krylov-Tikhonov methods, which merge an iterative and a direct approach to regularisation. In particular, strategies for choosing the regularization parameter and the regularization matrix will be emphasised.

• Speaker: Silvia Gazzola (University of Bath)
• Thursday 23 February 2017, 15:00–16:00
• Venue: MR 14, CMS.
• Series: Applied and Computational Analysis; organiser: Carola-Bibiane Schoenlieb.