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A new hybrid approach on WCET analysis for real-time systems using machine learning

dc.contributor.authorHuybrechts, Thomas
dc.contributor.authorMercelis, Siegfried
dc.contributor.authorHellinckx, Peter
dc.date.accessioned2021-10-25T20:04:20Z
dc.date.available2021-10-25T20:04:20Z
dc.date.issued2018
dc.identifier.urihttps://imec-publications.be/handle/20.500.12860/30925
dc.sourceIIOimport
dc.titleA new hybrid approach on WCET analysis for real-time systems using machine learning
dc.typeProceedings paper
dc.contributor.imecauthorHuybrechts, Thomas
dc.contributor.imecauthorMercelis, Siegfried
dc.contributor.imecauthorHellinckx, Peter
dc.contributor.orcidimecHuybrechts, Thomas::0000-0002-5611-6331
dc.contributor.orcidimecMercelis, Siegfried::0000-0001-9355-6566
dc.date.embargo9999-12-31
dc.source.peerreviewyes
dc.source.beginpage05:01
dc.source.endpage05:12
dc.source.conference18th International Workshop on Worst-Case Execution Time Analysis - WCET
dc.source.conferencedate6/07/2018
dc.source.conferencelocationBarcelona Spain
dc.identifier.urlhttp://drops.dagstuhl.de/opus/volltexte/2018/9751/pdf/OASIcs-WCET-2018-5.pdf
imec.availabilityPublished - open access
imec.internalnotespublished in the OASIcs series; Vol. 63


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