Double MgO-Based Perpendicular Magnetic Tunnel Junction for Artificial Neuron
DC Field | Value | Language |
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dc.contributor.author | Kim, Dong Won | - |
dc.contributor.author | Yi, Woo Seok | - |
dc.contributor.author | Choi, Jin Young | - |
dc.contributor.author | Ashiba, Kei | - |
dc.contributor.author | Baek, Jong Ung | - |
dc.contributor.author | Jun, Han Sol | - |
dc.contributor.author | Kim, Jae Joon | - |
dc.contributor.author | Park, Jea Gun | - |
dc.date.accessioned | 2021-08-02T09:50:58Z | - |
dc.date.available | 2021-08-02T09:50:58Z | - |
dc.date.created | 2021-05-12 | - |
dc.date.issued | 2020-04 | - |
dc.identifier.issn | 1662-4548 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/10552 | - |
dc.description.abstract | A perpendicular spin transfer torque (p-STT)-based neuron was developed for a spiking neural network (SNN). It demonstrated the integration behavior of a typical neuron in an SNN; in particular, the integration behavior corresponding to magnetic resistance change gradually increased with the input spike number. This behavior occurred when the spin electron directions between double Co2Fe6B2 free and pinned layers in the p-STT-based neuron were switched from parallel to antiparallel states. In addition, a neuron circuit for integrate-and-fire operation was proposed. Finally, pattern-recognition simulation was performed for a single-layer SNN. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | FRONTIERS MEDIA SA | - |
dc.title | Double MgO-Based Perpendicular Magnetic Tunnel Junction for Artificial Neuron | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Park, Jea Gun | - |
dc.identifier.doi | 10.3389/fnins.2020.00309 | - |
dc.identifier.scopusid | 2-s2.0-85084738260 | - |
dc.identifier.wosid | 000536180200001 | - |
dc.identifier.bibliographicCitation | FRONTIERS IN NEUROSCIENCE, v.14, pp.1 - 9 | - |
dc.relation.isPartOf | FRONTIERS IN NEUROSCIENCE | - |
dc.citation.title | FRONTIERS IN NEUROSCIENCE | - |
dc.citation.volume | 14 | - |
dc.citation.startPage | 1 | - |
dc.citation.endPage | 9 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | Y | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Neurosciences & Neurology | - |
dc.relation.journalWebOfScienceCategory | Neurosciences | - |
dc.subject.keywordPlus | MODEL | - |
dc.subject.keywordAuthor | neuromorphic | - |
dc.subject.keywordAuthor | MRAM | - |
dc.subject.keywordAuthor | spiking neuron | - |
dc.subject.keywordAuthor | spiking neural network | - |
dc.subject.keywordAuthor | artificial neuron | - |
dc.identifier.url | https://www.frontiersin.org/articles/10.3389/fnins.2020.00309/full | - |
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