Tracking Recurring Patterns in Time Series Using Dynamic Time Warping

被引：3
|
作者：
van der Vlist, Rik [1 ,2 ]
Taal, Cees [1 ]
Heusdens, Richard [2 ]
机构：
[1] Quby BV, Amsterdam, Netherlands
[2] Delft Univ Technol, Delft, Netherlands
来源：
2019 27TH EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO) | 2019年
关键词：
dynamic programming; dynamic time warping; time series analysis; SIGNALS;
D O I：
10.23919/eusipco.2019.8903102
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Dynamic time warping (DTW) is a distance measure to compare time series that exhibit similar patterns. In this paper, we will show how the warping path of the DTW algorithm can be interpreted, and a framework is proposed to extend the DTW algorithm. Using this framework, we will show how the dynamic programming structure of the DTW algorithm can be used to track repeating patterns in time series.
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收藏
页数：5
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