{"title":"神经网络用FPGA作为神经元,用IGZO薄膜作为突触","authors":"Yuki Koga, T. Matsuda, M. Kimura","doi":"10.1109/AM-FPD.2016.7543656","DOIUrl":null,"url":null,"abstract":"Neural networks are computing models based on human brains. We propose a neural network using a field-programmable gate array (FPGA) for neurons and amorphous In-Ga-Zn-O (a-IGZO) thin films for synapses. It is found that electric current in the a-IGZO thin film gradually decreases along the time. On the other hand, the degradation does not occur when light is irradiated. These phenomena can be utilized for the synapses in the neural network. It is confirmed that after the learning, the neural network replies the correct answer of AND logic. These results indicate that the neural networks using a-IGZO thin films have a great potential to realize future neural networks.","PeriodicalId":422453,"journal":{"name":"2016 23rd International Workshop on Active-Matrix Flatpanel Displays and Devices (AM-FPD)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Neural network using FPGA for neurons and IGZO thin films for synapses\",\"authors\":\"Yuki Koga, T. Matsuda, M. Kimura\",\"doi\":\"10.1109/AM-FPD.2016.7543656\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Neural networks are computing models based on human brains. We propose a neural network using a field-programmable gate array (FPGA) for neurons and amorphous In-Ga-Zn-O (a-IGZO) thin films for synapses. It is found that electric current in the a-IGZO thin film gradually decreases along the time. On the other hand, the degradation does not occur when light is irradiated. These phenomena can be utilized for the synapses in the neural network. It is confirmed that after the learning, the neural network replies the correct answer of AND logic. These results indicate that the neural networks using a-IGZO thin films have a great potential to realize future neural networks.\",\"PeriodicalId\":422453,\"journal\":{\"name\":\"2016 23rd International Workshop on Active-Matrix Flatpanel Displays and Devices (AM-FPD)\",\"volume\":\"16 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-07-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 23rd International Workshop on Active-Matrix Flatpanel Displays and Devices (AM-FPD)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AM-FPD.2016.7543656\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 23rd International Workshop on Active-Matrix Flatpanel Displays and Devices (AM-FPD)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AM-FPD.2016.7543656","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Neural network using FPGA for neurons and IGZO thin films for synapses
Neural networks are computing models based on human brains. We propose a neural network using a field-programmable gate array (FPGA) for neurons and amorphous In-Ga-Zn-O (a-IGZO) thin films for synapses. It is found that electric current in the a-IGZO thin film gradually decreases along the time. On the other hand, the degradation does not occur when light is irradiated. These phenomena can be utilized for the synapses in the neural network. It is confirmed that after the learning, the neural network replies the correct answer of AND logic. These results indicate that the neural networks using a-IGZO thin films have a great potential to realize future neural networks.