{"title":"用于人工神经网络的IGZO纳米光纤光电突触","authors":"Yixin Zhu, C. Wan","doi":"10.1109/EDTM53872.2022.9798355","DOIUrl":null,"url":null,"abstract":"Photoelectric synapses have attracted intensive attention due to their ultra-fast signal transmission, high bandwidth, low crosstalk and energy consumption. We proposed an indium gallium zinc oxide (IGZO) nanofiber based photoelectric synapse. The device has been demonstrated with versatile capabilities in mimicking biological synapse and the potential for constructing artificial neural networks (ANNs) with 5 bits precision and 15 fJ weight updating energy.","PeriodicalId":158478,"journal":{"name":"2022 6th IEEE Electron Devices Technology & Manufacturing Conference (EDTM)","volume":"1766 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"IGZO Nanofiber Photoelectric Synapse for Artificial Neural Networks\",\"authors\":\"Yixin Zhu, C. Wan\",\"doi\":\"10.1109/EDTM53872.2022.9798355\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Photoelectric synapses have attracted intensive attention due to their ultra-fast signal transmission, high bandwidth, low crosstalk and energy consumption. We proposed an indium gallium zinc oxide (IGZO) nanofiber based photoelectric synapse. The device has been demonstrated with versatile capabilities in mimicking biological synapse and the potential for constructing artificial neural networks (ANNs) with 5 bits precision and 15 fJ weight updating energy.\",\"PeriodicalId\":158478,\"journal\":{\"name\":\"2022 6th IEEE Electron Devices Technology & Manufacturing Conference (EDTM)\",\"volume\":\"1766 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-03-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 6th IEEE Electron Devices Technology & Manufacturing Conference (EDTM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/EDTM53872.2022.9798355\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 6th IEEE Electron Devices Technology & Manufacturing Conference (EDTM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EDTM53872.2022.9798355","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
IGZO Nanofiber Photoelectric Synapse for Artificial Neural Networks
Photoelectric synapses have attracted intensive attention due to their ultra-fast signal transmission, high bandwidth, low crosstalk and energy consumption. We proposed an indium gallium zinc oxide (IGZO) nanofiber based photoelectric synapse. The device has been demonstrated with versatile capabilities in mimicking biological synapse and the potential for constructing artificial neural networks (ANNs) with 5 bits precision and 15 fJ weight updating energy.
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