Efficient Frequency-Domain Uncertainty Quantification Using Parameterized Model Order Reduction

Francesco Ferranti, D. Romano, L. Lombardi, Giulio Antonini, Y. Tao, Michel Nakhla

Onderzoeksoutput: Conference paperResearch

Samenvatting

A parameterized model order reduction technique is investigated for the efficient frequency-domain uncertainty quantification of circuits obtained by the Partial Element Equivalent Circuit method. The parameterized model order reduction technique is coupled with a standard MC analysis and it is able to provide accurate uncertainty quantification results at a significantly reduced computational cost. Choosing the order of the parameterized model order reduction model is an important step depending on the detail of statistical information needed from the uncertainty quantification process. A practical approach is used for order selection. Numerical results for correlated random variables have validated the efficiency and accuracy of the proposed uncertainty quantification method.
Originele taal-2English
TitelEfficient Frequency-Domain Uncertainty Quantification Using Parameterized Model Order Reduction
UitgeverijIEEE
Pagina's868-872
Aantal pagina's5
ISBN van elektronische versie9781665407878
DOI's
StatusPublished - 2022
Evenement2022 International Symposium on Electromagnetic Compatibility (EMC EUROPE 2022) - Gothenburg, Sweden
Duur: 5 sep 20228 sep 2022

Publicatie series

NaamIEEE International Symposium on Electromagnetic Compatibility
Volume2022-September
ISSN van geprinte versie1077-4076
ISSN van elektronische versie2158-1118

Conference

Conference2022 International Symposium on Electromagnetic Compatibility (EMC EUROPE 2022)
Land/RegioSweden
StadGothenburg
Periode5/09/228/09/22

Bibliografische nota

Publisher Copyright:
© 2022 IEEE.

Copyright:
Copyright 2022 Elsevier B.V., All rights reserved.

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