A Novel Structured Single Device Neuron for Low Standby Power and Compact System Application

Cited 1 time in webofscience Cited 0 time in scopus
  • Hit : 149
  • Download : 0
DC FieldValueLanguage
dc.contributor.authorLee, Gyusoupko
dc.contributor.authorOh, Jungyeopko
dc.contributor.authorShin, Eui Joongko
dc.contributor.authorKim, Seonghoko
dc.contributor.authorPark, YoungKeunko
dc.contributor.authorKim, Min Juko
dc.contributor.authorChoi, Sung-Yoolko
dc.contributor.authorCho, Byung-Jinko
dc.date.accessioned2023-03-25T04:00:37Z-
dc.date.available2023-03-25T04:00:37Z-
dc.date.created2023-03-23-
dc.date.created2023-03-23-
dc.date.issued2023-03-
dc.identifier.citationIEEE ELECTRON DEVICE LETTERS, v.44, no.3, pp.528 - 531-
dc.identifier.issn0741-3106-
dc.identifier.urihttp://hdl.handle.net/10203/305778-
dc.description.abstractWe propose a single device neuron that utilizes a ferroelectric layer, a split gate, and a truncated floating gate structure. The proposed neuron device, named Single-Device Leaky-FeFET (SD L-FeFET), successfully emulates the neuronal dynamics for both excitatory and inhibitory connections while reducing the standby power by eliminating tail current. A spiking neural network (SNN) using the newly developed SD L-FeFET neuron shows MNIST handwriting digit pattern recognition of 92.5% and face recognition of 91.7%, which is comparable performance to the state-of-art SNN simulation results using conventional complex cell designs.-
dc.languageEnglish-
dc.publisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC-
dc.titleA Novel Structured Single Device Neuron for Low Standby Power and Compact System Application-
dc.typeArticle-
dc.identifier.wosid000965607300001-
dc.identifier.scopusid2-s2.0-85148668278-
dc.type.rimsART-
dc.citation.volume44-
dc.citation.issue3-
dc.citation.beginningpage528-
dc.citation.endingpage531-
dc.citation.publicationnameIEEE ELECTRON DEVICE LETTERS-
dc.identifier.doi10.1109/LED.2023.3240419-
dc.contributor.localauthorChoi, Sung-Yool-
dc.contributor.localauthorCho, Byung-Jin-
dc.contributor.nonIdAuthorKim, Min Ju-
dc.description.isOpenAccessN-
dc.type.journalArticleArticle-
dc.subject.keywordAuthorBio-inspired neuron-
dc.subject.keywordAuthorleaky integration-and-firing (LIF) neuron-
dc.subject.keywordAuthorferroelectric devices-
dc.subject.keywordAuthorsingle device neuron-
dc.subject.keywordAuthorneuromorphic computing-
dc.subject.keywordAuthorspiking neural network (SNN)-
Appears in Collection
EE-Journal Papers(저널논문)
Files in This Item
There are no files associated with this item.
This item is cited by other documents in WoS
⊙ Detail Information in WoSⓡ Click to see webofscience_button
⊙ Cited 1 items in WoS Click to see citing articles in records_button

qr_code

  • mendeley

    citeulike


rss_1.0 rss_2.0 atom_1.0