ℒ2-Optimal Reduced-Order Modeling Using Parameter-Separable Forms

Simple item page
dc.contributor.authorMlinaric, Petaren
dc.contributor.authorGugercin, Serkanen
dc.date.accessioned2023-12-21T15:26:33Zen
dc.date.available2023-12-21T15:26:33Zen
dc.date.issued2023-04-26en
dc.description.abstractWe provide a unifying framework for L-optimal reduced-order modeling for linear time-invariant dynamical systems and stationary parametric problems. Using parameter-separable forms of the reduced-model quantities, we derive the gradients of the L cost function with respect to the reduced matrices, which then allows a nonintrusive, data-driven, gradient-based descent algorithm to construct the optimal approximant using only output samples. By choosing an appropriate measure, the framework covers both continuous (Lebesgue) and discrete cost functions. We show the efficacy of the proposed algorithm via various numerical examples. Furthermore, we analyze under what conditions the data-driven approximant can be obtained via projection.en
dc.description.versionAccepted versionen
dc.format.extentPages A554-A578en
dc.format.extent25 page(s)en
dc.format.mimetypeapplication/pdfen
dc.identifier.doihttps://doi.org/10.1137/22M1500678en
dc.identifier.eissn1095-7197en
dc.identifier.issn1064-8275en
dc.identifier.issue2en
dc.identifier.orcidMlinaric, Petar [0000-0002-9437-7698]en
dc.identifier.urihttps://hdl.handle.net/10919/117252en
dc.identifier.volume45en
dc.language.isoenen
dc.publisherSIAM Publicationsen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectreduced-order modelingen
dc.subjectparametric stationary problemsen
dc.subjectlinear time-invariant systemsen
dc.subjectoptimizationen
dc.subjectG2 normen
dc.subjectnonlinear least squaresen
dc.titleℒ<inf>2</inf>-Optimal Reduced-Order Modeling Using Parameter-Separable Formsen
dc.title.serialSIAM Journal on Scientific Computingen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten
dc.type.otherArticleen
dc.type.otherJournalen
pubs.organisational-group/Virginia Techen
pubs.organisational-group/Virginia Tech/Scienceen
pubs.organisational-group/Virginia Tech/Science/Mathematicsen

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
siam.pdf
Size:
1.2 MB
Format:
Adobe Portable Document Format
Description:
Accepted version
Download
License bundle
Now showing 1 - 1 of 1
Name:
license.txt
Size:
1.5 KB
Format:
Plain Text
Description:
Download

Collections

All Faculty Deposits
Scholarly Works, Mathematics