FACTGen: Framework for Automated Circuit Topology Generator

Cited 0 time in webofscience Cited 0 time in scopus
  • Hit : 118
  • Download : 0
DC FieldValueLanguage
dc.contributor.authorSuh, Jangwonko
dc.contributor.authorJung, Wanyeongko
dc.date.accessioned2022-11-28T08:02:46Z-
dc.date.available2022-11-28T08:02:46Z-
dc.date.created2022-11-27-
dc.date.created2022-11-27-
dc.date.created2022-11-27-
dc.date.issued2022-10-20-
dc.identifier.citation19th International SoC Conference, ISOCC 2022-
dc.identifier.issn2163-9612-
dc.identifier.urihttp://hdl.handle.net/10203/301167-
dc.description.abstractBesides the popularity of computer-aided design methods, the circuit topology design itself still relies on human insights. We propose a framework for automated circuit topology generator (FACTGen). Our framework transforms the circuit topology generation problem into a continuous black-box optimization problem. FACTGen has succeeded to generate several 2T and 4T CMOS digital gate topologies.-
dc.languageEnglish-
dc.publisherThe Institute of Semiconductor Engineers-
dc.titleFACTGen: Framework for Automated Circuit Topology Generator-
dc.typeConference-
dc.identifier.wosid000971297000014-
dc.identifier.scopusid2-s2.0-85148454612-
dc.type.rimsCONF-
dc.citation.publicationname19th International SoC Conference, ISOCC 2022-
dc.identifier.conferencecountryKO-
dc.identifier.conferencelocationVirtual-
dc.contributor.localauthorJung, Wanyeong-
Appears in Collection
EE-Conference Papers(학술회의논문)
Files in This Item
There are no files associated with this item.

qr_code

  • mendeley

    citeulike


rss_1.0 rss_2.0 atom_1.0