{"title":"基于双串联忆阻器反向传播算法的片上硬件训练","authors":"H. Vo","doi":"10.1109/CCE.2018.8465750","DOIUrl":null,"url":null,"abstract":"This study proposes an architecture using two series memristor circuits as synapses to install the weights of the artificial neural network. Two series memristor circuit is similar to half-bridge circuit so here only to create positive weights in the range [0;1]. The use of two memristor circuit will decrease 50% the number of memristor. By proposed memristor circuit, we exploit back-propagation algorithm to train a three-bit odd parity on-chip hardware instead of software implementation.","PeriodicalId":118716,"journal":{"name":"2018 IEEE Seventh International Conference on Communications and Electronics (ICCE)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Training On-chip Hardware with Two Series Memristor Based Backpropagation Algorithm\",\"authors\":\"H. Vo\",\"doi\":\"10.1109/CCE.2018.8465750\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study proposes an architecture using two series memristor circuits as synapses to install the weights of the artificial neural network. Two series memristor circuit is similar to half-bridge circuit so here only to create positive weights in the range [0;1]. The use of two memristor circuit will decrease 50% the number of memristor. By proposed memristor circuit, we exploit back-propagation algorithm to train a three-bit odd parity on-chip hardware instead of software implementation.\",\"PeriodicalId\":118716,\"journal\":{\"name\":\"2018 IEEE Seventh International Conference on Communications and Electronics (ICCE)\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE Seventh International Conference on Communications and Electronics (ICCE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CCE.2018.8465750\",\"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 Seventh International Conference on Communications and Electronics (ICCE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCE.2018.8465750","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Training On-chip Hardware with Two Series Memristor Based Backpropagation Algorithm
This study proposes an architecture using two series memristor circuits as synapses to install the weights of the artificial neural network. Two series memristor circuit is similar to half-bridge circuit so here only to create positive weights in the range [0;1]. The use of two memristor circuit will decrease 50% the number of memristor. By proposed memristor circuit, we exploit back-propagation algorithm to train a three-bit odd parity on-chip hardware instead of software implementation.