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2020-02-25 Per Christian Hansen教授による講演会(その2)

投稿者:  相原 研輔(東京都市大学)
会場: 一橋大学 一橋講堂 2階 中会議室3
概要: Per Christian Hansen教授(デンマーク工科大学)をお招きし「IR Tools: a Matlab Package with Iterative Regularization Methods for Inverse Problems」という題目でご講演頂きます.本件は東京で開催する3つの講演会の2つ目です.

日程 2020年 2月 28日(金) 2:00PM-3:00PM → 25日(火) 3:30PM-4:30PM

* 開催日時が変更されました/time was changed
会場 国立情報学研究所(アクセス) 12階1212室 大学院講義室1

一橋大学 一橋講堂 2階 中会議室3 (access) /
Hitotsubashi University, National Center of Sciences Building, 2F, Medium Conference Room 3 (access)

* 会場が変更されました/the venue was changed
本文 この度,デンマーク工科大学のPer Christian Hansen教授をお招きし,下記の講演会を開催することとなりました.ご興味のある方は是非ご参加ください.

本件は東京で開催する3つの講演会の2つ目です.他2件は同日に一橋大学で,また,2月26日に東京都市大学にて開催されます.
This lecture is supported by Invitational Fellowships for Research in Japan (Short-term S).
Speaker Professor Per Christian Hansen
(DTU Compute, Technical University of Denmark) http://www2.compute.dtu.dk/~pcha/
Title IR Tools: a Matlab Package with Iterative Regularization Methods for Inverse Problems
Abstract We describe a new Matlab software package IR Tools with software for large-scale linear inverse problems. The package serves two purposes: we provide implementations of a range of iterative solvers, including several recently proposed methods that are not available elsewhere, and we provide a set of large-scale test problems in the form of discretizations of 2D linear inverse problems.

The solvers include iterative regularization methods where the regularization is due to the semi-convergence of the iterations, and Tikhonov-type formulations where the regularization is due to a regularization term. In both cases, we can impose bound constraints on the computed solutions. All the iterative methods are implemented in a very flexible fashion that allows the problem's coefficient matrix to be available as a (sparse) matrix, a function handle, or an object. The most basic call to all of the various iterative methods requires only this matrix and the right-hand side vector. If the method uses any special stopping criteria, regularization parameters, etc., then default values are set automatically by the code. With an optional input structure, the user can also have full control of any of the algorithm parameters.

The test problems represent realistic large-scale problems found in image reconstruction and several other applications. These new test problems are meant to replace the small and outdated test problems from 1994 in Regularization Tools. The basic call to all of the test problem generators produces a matrix, a right-hand side and the corresponding exact solution. Similar to the iterative methods, the user can use an optional input structure to control specific features of the test problem. We use numerical examples to illustrate the various algorithms and test problems available in this package.
This is joint work with Silvia Gazzola and James G. Nagy.
問い合わせ先 阿部 邦美,速水 謙
e-mail: abe@gifu.shotoku.ac.jp , hayamiseparatornii.ac.jp