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Analog CMOS-based resistive processing unit for deep neural network training
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| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Lee, Hyung-Min | - |
| dc.date.accessioned | 2021-08-28T06:23:56Z | - |
| dc.date.available | 2021-08-28T06:23:56Z | - |
| dc.date.created | 2021-04-22 | - |
| dc.date.issued | 2017-08-07 | - |
| dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/22981 | - |
| dc.publisher | IEEE | - |
| dc.title | Analog CMOS-based resistive processing unit for deep neural network training | - |
| dc.title.alternative | Analog CMOS-based resistive processing unit for deep neural network training | - |
| dc.type | Conference | - |
| dc.contributor.affiliatedAuthor | Lee, Hyung-Min | - |
| dc.identifier.bibliographicCitation | IEEE International Midwest Symposium on Circuits and Systems (MWSCAS), pp.422 - 425 | - |
| dc.relation.isPartOf | IEEE International Midwest Symposium on Circuits and Systems (MWSCAS) | - |
| dc.relation.isPartOf | International Midwest Symposium on Circuits and Systems (MWSCAS) | - |
| dc.citation.title | IEEE International Midwest Symposium on Circuits and Systems (MWSCAS) | - |
| dc.citation.startPage | 422 | - |
| dc.citation.endPage | 425 | - |
| dc.citation.conferencePlace | US | - |
| dc.citation.conferencePlace | Boston, MA, USA | - |
| dc.citation.conferenceDate | 2017-08-06 | - |
| dc.type.rims | CONF | - |
| dc.description.journalClass | 1 | - |
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