报告摘要: Over the last decade, a large number of time stepping schemes have been developed for time-fractional diffusion problems.
These schemes can be generally divided into: finite difference type, convolution quadrature type and discontinuous Galerkin methods.
Many of these methods are developed by assuming that the solution is sufficiently smooth, which however is generally not true.
In this talk, I will describe our recent works in analyzing and developing robust numerical schemes that do not assume solution regularity directly, but only data regularity.
报告人简介：Dr. Bangti Jin received Ph.D. degree in applied mathematics from the Chinese University of Hong Kong, Hong Kong, in 2008. Previously, he was an assistant Professor of mathematics at University of California, Riverside (2013-2014), a visiting assistant professor at Texas A&M University (2010-2013), an Alexandre von Humboldt Postdoctoral Researcher at the University of Bremen (2009-2010). He is currently a Reader in inverse problems in the Department of Computer Science, University College London, London, U.K. His research interests include computational inverse problems and numerical analysis of differential equations.