{"title":"利用IGZO作为人工神经网络突触的多层交叉点器件","authors":"Atsushi Kondc, M. Kimura, T. Matsuda","doi":"10.1109/IMFEDK.2018.8581976","DOIUrl":null,"url":null,"abstract":"We have developed a multilayer cross-point device using In-Ga-Zn-O semiconductor for synapse elements. There are 200 synapses on a glass substrates. We evaluate the change in the current value of the synapse. The current value gradually degrades by flowing current. The characteristic is available for modified Hebban learning.","PeriodicalId":434417,"journal":{"name":"2018 IEEE International Meeting for Future of Electron Devices, Kansai (IMFEDK)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Multilayer Cross-Point Device Using IGZO as Synapses in Artificial Neural Networks\",\"authors\":\"Atsushi Kondc, M. Kimura, T. Matsuda\",\"doi\":\"10.1109/IMFEDK.2018.8581976\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We have developed a multilayer cross-point device using In-Ga-Zn-O semiconductor for synapse elements. There are 200 synapses on a glass substrates. We evaluate the change in the current value of the synapse. The current value gradually degrades by flowing current. The characteristic is available for modified Hebban learning.\",\"PeriodicalId\":434417,\"journal\":{\"name\":\"2018 IEEE International Meeting for Future of Electron Devices, Kansai (IMFEDK)\",\"volume\":\"72 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE International Meeting for Future of Electron Devices, Kansai (IMFEDK)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IMFEDK.2018.8581976\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE International Meeting for Future of Electron Devices, Kansai (IMFEDK)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IMFEDK.2018.8581976","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Multilayer Cross-Point Device Using IGZO as Synapses in Artificial Neural Networks
We have developed a multilayer cross-point device using In-Ga-Zn-O semiconductor for synapse elements. There are 200 synapses on a glass substrates. We evaluate the change in the current value of the synapse. The current value gradually degrades by flowing current. The characteristic is available for modified Hebban learning.