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Impact of the leakage current of an AND-type synapse array on spiking neural networks

DC Field Value Language
dc.contributor.authorJeon, Bosung-
dc.contributor.authorSong, Seunghwan-
dc.contributor.authorHwang, Sungmin-
dc.contributor.authorJang, Taejin-
dc.contributor.authorPark, Kyungchul-
dc.contributor.authorPark, Jonghyuk-
dc.contributor.authorLee, Jong-Ho-
dc.contributor.authorPark, Byung-Gook-
dc.date.accessioned2022-10-05T04:40:43Z-
dc.date.available2022-10-05T04:40:43Z-
dc.date.created2022-07-27-
dc.date.issued2022-10-
dc.identifier.citationSolid-State Electronics, Vol.196, p. 108407-
dc.identifier.issn0038-1101-
dc.identifier.urihttps://hdl.handle.net/10371/185491-
dc.description.abstract© 2022In this paper, we analyze the impact of the leakage current of an AND-type synapse array on a spiking neural network (SNN). In order to evaluate the firing rate modulation affected by the leakage current of a synapse array, the electrical characteristics of a fabricated dual-gate synapse are measured and modeled. A SPICE circuit simulation shows a severe change in the firing rate in the SNN, and a system-level simulation with MNIST datasets exhibits frequency-dependent performance degradation due to the leakage current. Compared to a case with negligible leakage current, a 6.98% accuracy loss at 50 kHz of input frequency, which is the firing rate of conventional CMOS neurons.-
dc.language영어-
dc.publisherPergamon Press Ltd.-
dc.titleImpact of the leakage current of an AND-type synapse array on spiking neural networks-
dc.typeArticle-
dc.identifier.doi10.1016/j.sse.2022.108407-
dc.citation.journaltitleSolid-State Electronics-
dc.identifier.wosid000828207900001-
dc.identifier.scopusid2-s2.0-85133457773-
dc.citation.startpage108407-
dc.citation.volume196-
dc.description.isOpenAccessN-
dc.contributor.affiliatedAuthorLee, Jong-Ho-
dc.contributor.affiliatedAuthorPark, Byung-Gook-
dc.type.docTypeArticle-
dc.description.journalClass1-
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