RFID unreliable data filtering by integrating adaptive sliding Window and Euclidean distance

作     者：Li-Lan Liu Zi-Long Yuan Xue-Wei Liu Cheng Chen Ke-Sheng Wang 

作者机构：Shanghai Key Laboratory of Intelligent Manufacturing and RoboticsShanghai University Department of Production and Quality EngineeringNorwegian University of Science and TechnologyTrondheimNorway 

出 版 物：《Advances in Manufacturing》 (先进制造进展（英文版）)

年 卷 期：2014年第2卷第2期

页      面：121-129页

核心收录：

学科分类：1305[艺术学-设计学（可授艺术学、工学学位）] 13[艺术学] 081104[工学-模式识别与智能系统] 08[工学] 0804[工学-仪器科学与技术] 081101[工学-控制理论与控制工程] 0811[工学-控制科学与工程] 

基　　金：supported by the foundation of Science and Technology Commission of Shanghai Municipality (Grant No.13521103902) 

主　　题：Radio frequency identification(RFID) Adaptive sliding window Euclidean distance Redundant data 

摘      要：Through improving the redundant data filtering of unreliable data filter for radio frequency identification（RFID） with sliding-window,a data filter which integrates self-adaptive sliding-window and Euclidean distance is *** input data required being filtered have been shunt by considering a large number of redundant data existing in the unreliable data for RFID and the redundant data in RFID are the main filtering object with utilizing the filter based on Euclidean *** comparison between the results from the method proposed in this paper and previous research shows that it can improve the accuracy of the RFID for unreliable data filtering and largely reduce the redundant reading rate.