Tracking recurring patterns in time series using dynamic time warping
Conference Paper
(2019)
Author(s)
Rik Van Der Vlist (Student TU Delft, Quby B.V.)
Cees Taal (TU Delft - Multimedia Computing, Quby B.V.)
Richard Heusdens (TU Delft - Signal Processing Systems)
Research Group
Signal Processing Systems
DOI related publication
https://doi.org/10.23919/EUSIPCO.2019.8903102
To reference this document use:
https://resolver.tudelft.nl/uuid:fc145587-fb0f-40cb-ba98-3fb36a75ac03
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Publication Year
2019
Language
English
Research Group
Signal Processing Systems
Volume number
2019-September
ISBN (electronic)
9789082797039
Abstract
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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