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Multiplexed Complementary Signal Transmission for a Self-Regulating Artificial Nervous System

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dc.contributor.authorChoi, Young Jin-
dc.contributor.authorRoe, Dong Gue-
dc.contributor.authorChoi, Yoon Young-
dc.contributor.authorKim, Seongchan-
dc.contributor.authorJo, Sae Byeok-
dc.contributor.authorLee, Hwa Sung-
dc.contributor.authorKim, Do Hwan-
dc.contributor.authorCho, Jeong Ho-
dc.date.accessioned2023-05-03T09:37:42Z-
dc.date.available2023-05-03T09:37:42Z-
dc.date.issued2023-01-
dc.identifier.issn2198-3844-
dc.identifier.issn2198-3844-
dc.identifier.urihttps://scholarworks.bwise.kr/erica/handle/2021.sw.erica/112636-
dc.description.abstractNeuromorphic engineering has emerged as a promising research field that can enable efficient and sophisticated signal transmission by mimicking the biological nervous system. This paper presents an artificial nervous system capable of facile self-regulation via multiplexed complementary signals. Based on the tunable nature of the Schottky barrier of a complementary signal integration circuit, a pair of complementary signals is successfully integrated to realize efficient signal transmission. As a proof of concept, a feedback-based blood glucose level control system is constructed by incorporating a glucose/insulin sensor, a complementary signal integration circuit, an artificial synapse, and an artificial neuron circuit. Certain amounts of glucose and insulin in the initial state are detected by each sensor and reflected as positive and negative amplitudes of the multiplexed presynaptic pulses, respectively. Subsequently, the pulses are converted to postsynaptic current, which triggered the injection of glucose or insulin in a way that confined the glucose level to a desirable range. The proposed artificial nervous system demonstrates the notable potential of practical advances in complementary control engineering.-
dc.format.extent9-
dc.language영어-
dc.language.isoENG-
dc.publisherWiley-VCH Verlag-
dc.titleMultiplexed Complementary Signal Transmission for a Self-Regulating Artificial Nervous System-
dc.typeArticle-
dc.publisher.location미국-
dc.identifier.doi10.1002/advs.202205155-
dc.identifier.scopusid2-s2.0-85142859601-
dc.identifier.wosid000891043800001-
dc.identifier.bibliographicCitationAdvanced Science, v.10, no.3, pp 1 - 9-
dc.citation.titleAdvanced Science-
dc.citation.volume10-
dc.citation.number3-
dc.citation.startPage1-
dc.citation.endPage9-
dc.type.docTypeArticle; Early Access-
dc.description.isOpenAccessY-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaChemistry-
dc.relation.journalResearchAreaScience & Technology - Other Topics-
dc.relation.journalResearchAreaMaterials Science-
dc.relation.journalWebOfScienceCategoryChemistry, Multidisciplinary-
dc.relation.journalWebOfScienceCategoryNanoscience & Nanotechnology-
dc.relation.journalWebOfScienceCategoryMaterials Science, Multidisciplinary-
dc.subject.keywordPlusINSULIN-
dc.subject.keywordPlusINJECTION-
dc.subject.keywordPlusSYNAPSE-
dc.subject.keywordAuthorartificial nervous system-
dc.subject.keywordAuthorhealthcare-
dc.subject.keywordAuthormulti-level regulation-
dc.subject.keywordAuthorSchottky barrier transistor-
dc.subject.keywordAuthorsignal multiplexing-
dc.identifier.urlhttps://onlinelibrary.wiley.com/doi/10.1002/advs.202205155-
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ERICA 첨단융합대학 (ERICA 신소재·반도체공학전공)
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