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Article: Experimentally-Validated Crossbar Model for Defect-Aware Training of Neural Networks

TitleExperimentally-Validated Crossbar Model for Defect-Aware Training of Neural Networks
Authors
MAO, RWEN, BJIANG, MChen, JLi, C
Issue Date2022
Citation
IEEE Transactions on Circuits and Systems II: Express Briefs, 2022, v. 69, p. 2468-2472 How to Cite?
DOI: http://dx.doi.org/10.1109/TCSII.2022.3160591
Persistent Identifierhttp://hdl.handle.net/10722/313793
ISI Accession Number ID
WOS:000790814000020

 

DC FieldValueLanguage
dc.contributor.authorMAO, R-
dc.contributor.authorWEN, B-
dc.contributor.authorJIANG, M-
dc.contributor.authorChen, J-
dc.contributor.authorLi, C-
dc.date.accessioned2022-07-05T05:05:49Z-
dc.date.available2022-07-05T05:05:49Z-
dc.date.issued2022-
dc.identifier.citationIEEE Transactions on Circuits and Systems II: Express Briefs, 2022, v. 69, p. 2468-2472-
dc.identifier.urihttp://hdl.handle.net/10722/313793-
dc.languageeng-
dc.relation.ispartofIEEE Transactions on Circuits and Systems II: Express Briefs-
dc.titleExperimentally-Validated Crossbar Model for Defect-Aware Training of Neural Networks-
dc.typeArticle-
dc.identifier.emailLi, C: canl@hku.hk-
dc.identifier.authorityLi, C=rp02706-
dc.identifier.doi10.1109/TCSII.2022.3160591-
dc.identifier.hkuros333983-
dc.identifier.volume69-
dc.identifier.spage2468-
dc.identifier.epage2472-
dc.identifier.isiWOS:000790814000020-

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