DC FieldValueLanguage
dc.contributor.authorSchierholz, Morten-
dc.contributor.authorHassab, Youcef-
dc.contributor.authorYang, Cheng-
dc.contributor.authorSchuster, Christian-
dc.date.accessioned2022-01-12T13:46:12Z-
dc.date.available2022-01-12T13:46:12Z-
dc.date.issued2021-10-
dc.identifier.citationIEEE 30th Conference on Electrical Performance of Electronic Packaging and Systems (EPEPS 2021)de_DE
dc.identifier.isbn978-1-6654-4269-5de_DE
dc.identifier.urihttp://hdl.handle.net/11420/11472-
dc.description.abstractIn this paper the performance of support vector machines (SVMs) is investigated to classify printed circuit board (PCB) based power delivery networks (PDNs). For different decoupling capacitor (decap) distributions on a PCB the impedance of the PDN is evaluated. The target impedance (TI) is used as separation condition of the two classes meeting or violating the TI. It is shown that the preprocessing of the PCB parameters and decap distributions have a strong impact on the prediction accuracy of SVMs. Furthermore, variations of the PCB structure with respect to the geometry are investigated. It is shown using extended SVMs with geometry features as additional input feature that it is possible to achieve similar prediction accuracies in comparison with a collaboration of multiple SVMs. Finally the performance of power integrity (PI) classifications by SVMs in comparison with artificial neural networks (ANNs) is discussed.en
dc.language.isoende_DE
dc.titleEvaluation of Support Vector Machines for PCB based Power Delivery Network Classificationde_DE
dc.typeinProceedingsde_DE
dc.type.dinicontributionToPeriodical-
dcterms.DCMITypeText-
tuhh.abstract.englishIn this paper the performance of support vector machines (SVMs) is investigated to classify printed circuit board (PCB) based power delivery networks (PDNs). For different decoupling capacitor (decap) distributions on a PCB the impedance of the PDN is evaluated. The target impedance (TI) is used as separation condition of the two classes meeting or violating the TI. It is shown that the preprocessing of the PCB parameters and decap distributions have a strong impact on the prediction accuracy of SVMs. Furthermore, variations of the PCB structure with respect to the geometry are investigated. It is shown using extended SVMs with geometry features as additional input feature that it is possible to achieve similar prediction accuracies in comparison with a collaboration of multiple SVMs. Finally the performance of power integrity (PI) classifications by SVMs in comparison with artificial neural networks (ANNs) is discussed.de_DE
tuhh.publisher.doi10.1109/EPEPS51341.2021.9609190-
tuhh.publication.instituteTheoretische Elektrotechnik E-18de_DE
tuhh.type.opusInProceedings (Aufsatz / Paper einer Konferenz etc.)-
dc.type.drivercontributionToPeriodical-
dc.type.casraiConference Paper-
tuhh.container.startpage1de_DE
tuhh.container.endpage3de_DE
dc.relation.conferenceIEEE 30th Conference on Electrical Performance of Electronic Packaging and Systems (EPEPS 2021)de_DE
dc.identifier.scopus2-s2.0-85123199362de_DE
datacite.resourceTypeConference Paper-
datacite.resourceTypeGeneralText-
item.cerifentitytypePublications-
item.openairetypeinProceedings-
item.creatorOrcidSchierholz, Morten-
item.creatorOrcidHassab, Youcef-
item.creatorOrcidYang, Cheng-
item.creatorOrcidSchuster, Christian-
item.creatorGNDSchierholz, Morten-
item.creatorGNDHassab, Youcef-
item.creatorGNDYang, Cheng-
item.creatorGNDSchuster, Christian-
item.languageiso639-1en-
item.fulltextNo Fulltext-
item.mappedtypeinProceedings-
item.grantfulltextnone-
item.openairecristypehttp://purl.org/coar/resource_type/c_5794-
crisitem.author.deptTheoretische Elektrotechnik E-18-
crisitem.author.deptTheoretische Elektrotechnik E-18-
crisitem.author.deptTheoretische Elektrotechnik E-18-
crisitem.author.orcid0000-0003-4404-8383-
crisitem.author.orcid0000-0001-9184-5030-
crisitem.author.orcid0000-0003-4019-0788-
crisitem.author.parentorgStudiendekanat Elektrotechnik, Informatik und Mathematik (E)-
crisitem.author.parentorgStudiendekanat Elektrotechnik, Informatik und Mathematik (E)-
crisitem.author.parentorgStudiendekanat Elektrotechnik, Informatik und Mathematik (E)-
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