{"title":"基于脉冲密度调制的全数字神经网络实现","authors":"J. Tomberg, T. Ritoniemi, K. Kaski, H. Tenhunen","doi":"10.1109/CICC.1989.56744","DOIUrl":null,"url":null,"abstract":"An efficient implementation of a Hopfield-type fully connected neural-network architecture is presented that is based on a pulse-density modulation technique implemented by using fully digital structures. The synaptic weights are programmable, and thus the area of one synapse and the entire network depends on the resolution of the weight. Advantages of the design are its modularity and expandability","PeriodicalId":165054,"journal":{"name":"1989 Proceedings of the IEEE Custom Integrated Circuits Conference","volume":"35 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1989-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"27","resultStr":"{\"title\":\"Fully digital neural network implementation based on pulse density modulation\",\"authors\":\"J. Tomberg, T. Ritoniemi, K. Kaski, H. Tenhunen\",\"doi\":\"10.1109/CICC.1989.56744\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An efficient implementation of a Hopfield-type fully connected neural-network architecture is presented that is based on a pulse-density modulation technique implemented by using fully digital structures. The synaptic weights are programmable, and thus the area of one synapse and the entire network depends on the resolution of the weight. Advantages of the design are its modularity and expandability\",\"PeriodicalId\":165054,\"journal\":{\"name\":\"1989 Proceedings of the IEEE Custom Integrated Circuits Conference\",\"volume\":\"35 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1989-05-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"27\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"1989 Proceedings of the IEEE Custom Integrated Circuits Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CICC.1989.56744\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"1989 Proceedings of the IEEE Custom Integrated Circuits Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CICC.1989.56744","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Fully digital neural network implementation based on pulse density modulation
An efficient implementation of a Hopfield-type fully connected neural-network architecture is presented that is based on a pulse-density modulation technique implemented by using fully digital structures. The synaptic weights are programmable, and thus the area of one synapse and the entire network depends on the resolution of the weight. Advantages of the design are its modularity and expandability
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