标题:A New Method of Real-time Detection of Changes in Periodic Data-stream
作者:Lyu, Chen; Lu, Guoliang; Cheng, Bin; Zheng, Xiangwei
作者机构:[Lyu, Chen; Zheng, Xiangwei] Shandong Normal Univ, Sch Informat Sci & Engn, Shandong Prov Key Lab Novel Distributed Comp Soft, Jinan, Shandong, People 更多
会议名称:9th International Conference on Digital Image Processing (ICDIP)
会议日期:MAY 19-22, 2017
来源:NINTH INTERNATIONAL CONFERENCE ON DIGITAL IMAGE PROCESSING (ICDIP 2017)
出版年:2017
卷:10420
DOI:10.1117/12.2281699
关键词:Change point; periodic time series; martingale-test; anomaly measure
摘要:The change point detection in periodic time series is much desirable in many practical usages. We present a novel algorithm for this task, which includes two phases: 1) anomaly measure-on the basis of a typical regression model, we propose a new computation method to measure anomalies in time series which does not require any reference data from other measurement(s); 2) change detection-we introduce a new martingale test for detection which can be operated in an unsupervised and nonparametric way. We have conducted extensive experiments to systematically test our algorithm. The results make us believe that our algorithm can be directly applicable in many real-world change-point-detection applications.
收录类别:CPCI-S;EI;SCOPUS
资源类型:会议论文;期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85030714178&doi=10.1117%2f12.2281699&partnerID=40&md5=c06a3ea3c37f35b968e92a7a53afd106
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