Tracking recurring patterns in time series using dynamic time warping

Rik Van Der Vlist; Cees Taal; Richard Heusdens

doi:10.23919/EUSIPCO.2019.8903102

Tracking recurring patterns in time series using dynamic time warping

Rik Van Der Vlist, Cees Taal, Richard Heusdens

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

9 Citations (Scopus)

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.

Original language	English
Title of host publication	EUSIPCO 2019 - 27th European Signal Processing Conference
Publisher	European Signal Processing Conference, EUSIPCO
Number of pages	5
Volume	2019-September
ISBN (Electronic)	9789082797039
DOIs	https://doi.org/10.23919/EUSIPCO.2019.8903102
Publication status	Published - 1 Sept 2019
Event	27th European Signal Processing Conference, EUSIPCO 2019 - A Coruna, Spain Duration: 2 Sept 2019 → 6 Sept 2019

Conference

Conference	27th European Signal Processing Conference, EUSIPCO 2019
Country/Territory	Spain
City	A Coruna
Period	2/09/19 → 6/09/19

Keywords

Dynamic programming
Dynamic time warping
Time series analysis

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10.23919/EUSIPCO.2019.8903102

Cite this

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title = "Tracking recurring patterns in time series using dynamic time warping",

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.",

keywords = "Dynamic programming, Dynamic time warping, Time series analysis",

author = "{Van Der Vlist}, Rik and Cees Taal and Richard Heusdens",

year = "2019",

month = sep,

day = "1",

doi = "10.23919/EUSIPCO.2019.8903102",

language = "English",

volume = "2019-September",

booktitle = "EUSIPCO 2019 - 27th European Signal Processing Conference",

publisher = "European Signal Processing Conference, EUSIPCO",

note = "27th European Signal Processing Conference, EUSIPCO 2019 ; Conference date: 02-09-2019 Through 06-09-2019",

}

Van Der Vlist, R, Taal, C & Heusdens, R 2019, Tracking recurring patterns in time series using dynamic time warping. in EUSIPCO 2019 - 27th European Signal Processing Conference. vol. 2019-September, European Signal Processing Conference, EUSIPCO, 27th European Signal Processing Conference, EUSIPCO 2019, A Coruna, Spain, 2/09/19. https://doi.org/10.23919/EUSIPCO.2019.8903102

Tracking recurring patterns in time series using dynamic time warping. / Van Der Vlist, Rik; Taal, Cees; Heusdens, Richard.
EUSIPCO 2019 - 27th European Signal Processing Conference. Vol. 2019-September European Signal Processing Conference, EUSIPCO, 2019.

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

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AU - Taal, Cees

AU - Heusdens, Richard

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Y1 - 2019/9/1

N2 - 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.

AB - 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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KW - Time series analysis

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DO - 10.23919/EUSIPCO.2019.8903102

M3 - Conference contribution

AN - SCOPUS:85075606316

VL - 2019-September

BT - EUSIPCO 2019 - 27th European Signal Processing Conference

PB - European Signal Processing Conference, EUSIPCO

T2 - 27th European Signal Processing Conference, EUSIPCO 2019

Y2 - 2 September 2019 through 6 September 2019

ER -

Tracking recurring patterns in time series using dynamic time warping

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