Preprint Open Access

# Maximum Entropy Snapshot Sampling for Reduced Basis Modelling

Bannenberg, M.W.F.M.; Kasolis, F.; Günther, M.; Clemens, M.

### DataCite XML Export

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<identifier identifierType="DOI">10.5281/zenodo.4542806</identifier>
<creators>
<creator>
<creatorName>Bannenberg, M.W.F.M.</creatorName>
<givenName>M.W.F.M.</givenName>
<familyName>Bannenberg</familyName>
<affiliation>University of Wuppertal</affiliation>
</creator>
<creator>
<creatorName>Kasolis, F.</creatorName>
<givenName>F.</givenName>
<familyName>Kasolis</familyName>
<affiliation>University of Wuppertal</affiliation>
</creator>
<creator>
<creatorName>Günther, M.</creatorName>
<givenName>M.</givenName>
<familyName>Günther</familyName>
<affiliation>University of Wuppertal</affiliation>
</creator>
<creator>
<creatorName>Clemens, M.</creatorName>
<givenName>M.</givenName>
<familyName>Clemens</familyName>
<affiliation>University of Wuppertal</affiliation>
</creator>
</creators>
<titles>
<title>Maximum Entropy Snapshot Sampling for Reduced Basis Modelling</title>
</titles>
<publisher>Zenodo</publisher>
<publicationYear>2020</publicationYear>
<subjects>
<subject>Circuit models, entropy, nonlinear model reduction, QR decomposition</subject>
</subjects>
<dates>
<date dateType="Issued">2020-10-20</date>
</dates>
<language>en</language>
<resourceType resourceTypeGeneral="Text">Preprint</resourceType>
<alternateIdentifiers>
<alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/4542806</alternateIdentifier>
</alternateIdentifiers>
<relatedIdentifiers>
<relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.4542805</relatedIdentifier>
<relatedIdentifier relatedIdentifierType="URL" relationType="IsPartOf">https://zenodo.org/communities/romsoc</relatedIdentifier>
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<rightsList>
<rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
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<descriptions>
<description descriptionType="Abstract">&lt;p&gt;The so-called maximum entropy snapshot sampling method is employed for reducing two nonlinear circuit models. The maximum entropy snapshot sampling directly reduces the number of snapshots by recursively identifying and selecting the snapshots that strictly increase an estimate of the correlation entropy of the considered systems. Reduced bases are then obtained with the orthogonal-triangular decomposition. In the first case study, the resulting overdetermined systems are solved in the least squares sense. In the second case study, the basis is incorporated in a reduced order multirate scheme, whilst the reduction parameter is estimated through an optimality requirement. Numerical experiments verify the performance of the advocated approach, in terms of computational costs and accuracy, relative to an established reduction framework that is based on the singular value decomposition.&lt;/p&gt;</description>
<description descriptionType="Other">Preprint BUW-IMACM 20/46, Institute of Mathematical Modelling, Analysis and Computational Mathematics (IMACM), Bergische Universität Wuppertal, October 2020</description>
</descriptions>
<fundingReferences>
<fundingReference>
<funderName>European Commission</funderName>
<funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/501100000780</funderIdentifier>
<awardNumber awardURI="info:eu-repo/grantAgreement/EC/H2020/765374/">765374</awardNumber>
<awardTitle>Reduced Order Modelling, Simulation and Optimization of Coupled systems</awardTitle>
</fundingReference>
</fundingReferences>
</resource>

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