A Machine Learning-Based Epistemic Modeling Framework for EMC and SI Assessment

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dc.contributor.author	Kan, Duygu
dc.contributor.author	De Ridder, Simon
dc.contributor.author	Spina, Domenico
dc.contributor.author	Grassi, Flavia
dc.date.accessioned	2021-11-02T16:03:22Z
dc.date.available	2021-11-02T16:03:22Z
dc.date.issued	2020
dc.identifier.issn	2475-9481
dc.identifier.other	WOS:000628989600009
dc.identifier.uri	https://imec-publications.be/handle/20.500.12860/38051
dc.source	WOS
dc.title	A Machine Learning-Based Epistemic Modeling Framework for EMC and SI Assessment
dc.type	Proceedings paper
dc.contributor.imecauthor	Kan, Duygu
dc.contributor.imecauthor	De Ridder, Simon
dc.contributor.imecauthor	Spina, Domenico
dc.contributor.orcidimec	Kan, Duygu::0000-0001-8789-9087
dc.contributor.orcidimec	Spina, Domenico::0000-0003-2379-5259
dc.identifier.eisbn	978-1-7281-4204-3
dc.source.numberofpages	4
dc.source.peerreview	yes
dc.source.conference	24th IEEE Workshop on Signal and Power Integrity (SPI)
dc.source.conferencedate	MAY 17-20, 2020
dc.source.conferencelocation	Cologne
imec.availability	Under review

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Version	Item	Date	Summary
2	20.500.12860/38051.2	2022-01-05T10:21:35Z	validation by library/open access desk
1	20.500.12860/38051*	2021-11-02T16:03:22Z