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Cited 2 time in webofscience Cited 1 time in scopus
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Two phase-change memory (2-PCM) neurons for implementing a backpropagation algorithm

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dc.contributor.authorLi, Cheng-
dc.contributor.authorAn, Junseop-
dc.contributor.authorKweon, Jun Young-
dc.contributor.authorSong, Yun Heub-
dc.date.accessioned2021-07-30T04:54:47Z-
dc.date.available2021-07-30T04:54:47Z-
dc.date.issued2020-04-
dc.identifier.issn0021-4922-
dc.identifier.issn1347-4065-
dc.identifier.urihttps://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/2070-
dc.description.abstractIn this paper, we proposed a neuron circuit, i.e. a two phase-change memory (2-PCM) neuron, to implement a backpropagation algorithm for hardware neural networks. PCM devices in the neuron are used for computing and storing signals. One of the PCM devices is used for storing the forward propagation (FP) signal, and the other is used for storing the backpropagation signal, This paper presents a new application of;PCM devices in traditional artificial neural networks. With the proposed;2-PCM neuron circuits, the neuron circuits need not to remain powered during the entire process for temporarily storing the FP signals. And it does not require additional memory for storing backpropagation signals. In addition, the two PCM devices share a common read and write driver circuits.-
dc.format.extent8-
dc.language영어-
dc.language.isoENG-
dc.publisherIOP Publishing Ltd-
dc.titleTwo phase-change memory (2-PCM) neurons for implementing a backpropagation algorithm-
dc.typeArticle-
dc.publisher.location영국-
dc.identifier.doi10.35848/1347-4065/ab6a2b-
dc.identifier.scopusid2-s2.0-85083317119-
dc.identifier.wosid000519630000022-
dc.identifier.bibliographicCitationJapanese Journal of Applied Physics, v.59, no.SG, pp 1 - 8-
dc.citation.titleJapanese Journal of Applied Physics-
dc.citation.volume59-
dc.citation.numberSG-
dc.citation.startPage1-
dc.citation.endPage8-
dc.type.docTypeArticle; Proceedings Paper-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaPhysics-
dc.relation.journalWebOfScienceCategoryPhysics, Applied-
dc.subject.keywordPlusBackpropagation-
dc.subject.keywordPlusNeural networks-
dc.subject.keywordPlusNeurons-
dc.subject.keywordPlusPhase change memory-
dc.subject.keywordPlusDriver circuit-
dc.subject.keywordPlusForward propagation-
dc.subject.keywordPlusHardware neural networks-
dc.subject.keywordPlusNeuron circuits-
dc.subject.keywordPlusNew applications-
dc.subject.keywordPlusTwo phase-
dc.identifier.urlhttps://iopscience.iop.org/article/10.35848/1347-4065/ab6a2b-
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