Local Parametrization of Subspaces on Matrix Manifolds via Derivative Information

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

A method is proposed for constructing local parametrizations of
orthogonal bases and of subspaces by computing
trajectories in the Stiefel and the Grassmann manifold, respectively.
The trajectories are obtained by exploiting sensitivity information
on the singular value decomposition with respect to parametric changes and
a Taylor-like local linearization suitably adapted to the underlying manifold structure.
An important practical application of the proposed approach is
parametric model reduction (pMOR).
The connection with pMOR is discussed in detail and the results are illustrated by numerical experiment.
Original languageEnglish
Title of host publicationNumerical Mathematics and Advanced Applications : ENUMATH 2015
EditorsBulent Karasozen, Murat Manguoğlu, Münevver Tezer-Sezgin, Serdar Göktepe, Ömür Uğur
Volume112
PublisherSpringer
Publication dateDec 2016
Pages379-387
ChapterV Reduced Order Modeling
ISBN (Print)978-3-319-39927-0
ISBN (Electronic)978-3-319-39929-4
DOIs
Publication statusPublished - Dec 2016
Externally publishedYes
EventEuropean Conference on Numerical Mathematics and Advanced Applications - Middle East Technical University, Ankara, Turkey
Duration: 13. Sep 201518. Sep 2015
http://enumath2015.iam.metu.edu.tr/

Conference

ConferenceEuropean Conference on Numerical Mathematics and Advanced Applications
LocationMiddle East Technical University
Country/TerritoryTurkey
CityAnkara
Period13/09/201518/09/2015
Internet address
SeriesLecture Notes in Computational Science and Engineering
Volume112
ISSN1439-7358

Fingerprint

Dive into the research topics of 'Local Parametrization of Subspaces on Matrix Manifolds via Derivative Information'. Together they form a unique fingerprint.

Cite this