Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 오새룬터 | - |
dc.date.accessioned | 2021-08-31T07:05:52Z | - |
dc.date.available | 2021-08-31T07:05:52Z | - |
dc.date.issued | 2020-08 | - |
dc.identifier.citation | NATURE COMMUNICATIONS, v. 11, no. 1, page. 1-9 | en_US |
dc.identifier.issn | 2041-1723 | - |
dc.identifier.uri | https://www.proquest.com/docview/2431120841?accountid=11283 | - |
dc.identifier.uri | https://repository.hanyang.ac.kr/handle/20.500.11754/164734 | - |
dc.description.abstract | Brain-inspired parallel computing, which is typically performed using a hardware neuralnetwork platform consisting of numerous artificial synapses, is a promising technology for effectively handling large amounts of informational data. However, the reported nonlinear and asymmetric conductance-update characteristics of artificial synapses prevent a hardware neural-network from delivering the same high-level training and inference accuracies as those delivered by a software neural-network. Here, we developed an artificial van-der-Waals hybrid synapse that features linear and symmetric conductance-update characteristics. Tungsten diselenide and molybdenum disulfide channels were used selectively to potentiate and depress conductance. Subsequently, via training and inference simulation, we demonstrated the feasibility of our hybrid synapse toward a hardware neural-network and also delivered high recognition rates that were comparable to those delivered using a software neural-network. This simulation involving the use of acoustic patterns was performed with a neural network that was theoretically formed with the characteristics of the hybrid synapses. | en_US |
dc.description.sponsorship | This research was supported by the Basic Science Research Program, Basic Research Lab Program, and Nano-Material Technology Development Program through National Research Foundation of Korea (NRF) grants funded by the Korean government (MSIP) (2020R1A4A2002806, 2019M3F3A1A01074451, 2018R1A2A2A05020475, and 2016M3A7B4910426). | en_US |
dc.language.iso | en_US | en_US |
dc.publisher | NATURE PUBLISHING GROUP | en_US |
dc.title | Artificial van der Waals hybrid synapse and its application to acoustic pattern recognition | en_US |
dc.type | Article | en_US |
dc.relation.no | 1 | - |
dc.relation.volume | 11 | - |
dc.identifier.doi | 10.1038/s41467-020-17849-3 | - |
dc.relation.page | 1-9 | - |
dc.relation.journal | NATURE COMMUNICATIONS | - |
dc.contributor.googleauthor | Seo, S. | - |
dc.contributor.googleauthor | Kang, B.-S. | - |
dc.contributor.googleauthor | Lee, J.-J. | - |
dc.contributor.googleauthor | Ryu, H.-J. | - |
dc.contributor.googleauthor | Kim, S. | - |
dc.contributor.googleauthor | Kim, H. | - |
dc.contributor.googleauthor | Oh, S. | - |
dc.contributor.googleauthor | Heo, K | - |
dc.contributor.googleauthor | Park, J.-H. | - |
dc.contributor.googleauthor | Shim, J. | - |
dc.relation.code | 2020046258 | - |
dc.sector.campus | E | - |
dc.sector.daehak | COLLEGE OF ENGINEERING SCIENCES[E] | - |
dc.sector.department | DIVISION OF ELECTRICAL ENGINEERING | - |
dc.identifier.pid | sroonter | - |
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