{"title":"基于rfid的室内定位实时、近理想全息图","authors":"Haonan Chen, Dong Wang","doi":"10.1145/3131672.3136994","DOIUrl":null,"url":null,"abstract":"Through the investigation of the mathematical model of hologram-based indoor localization system using RFID, this paper reveals two potential deficiencies about accuracy and gives the machine learning interpretation of the model. Exploiting the methods from machine learning and the thought of hierarchy, the output accuracy and the efficiency of the model can be further boosted. Simulation and experiment show that the enhanced model can halve mean error and attain 9x execution speed improvement.","PeriodicalId":424262,"journal":{"name":"Proceedings of the 15th ACM Conference on Embedded Network Sensor Systems","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Real-time and Nearly Ideal Hologram for RFID-based Indoor Localization\",\"authors\":\"Haonan Chen, Dong Wang\",\"doi\":\"10.1145/3131672.3136994\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Through the investigation of the mathematical model of hologram-based indoor localization system using RFID, this paper reveals two potential deficiencies about accuracy and gives the machine learning interpretation of the model. Exploiting the methods from machine learning and the thought of hierarchy, the output accuracy and the efficiency of the model can be further boosted. Simulation and experiment show that the enhanced model can halve mean error and attain 9x execution speed improvement.\",\"PeriodicalId\":424262,\"journal\":{\"name\":\"Proceedings of the 15th ACM Conference on Embedded Network Sensor Systems\",\"volume\":\"26 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-11-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 15th ACM Conference on Embedded Network Sensor Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3131672.3136994\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 15th ACM Conference on Embedded Network Sensor Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3131672.3136994","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Real-time and Nearly Ideal Hologram for RFID-based Indoor Localization
Through the investigation of the mathematical model of hologram-based indoor localization system using RFID, this paper reveals two potential deficiencies about accuracy and gives the machine learning interpretation of the model. Exploiting the methods from machine learning and the thought of hierarchy, the output accuracy and the efficiency of the model can be further boosted. Simulation and experiment show that the enhanced model can halve mean error and attain 9x execution speed improvement.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
