Dynamic Time Warping Under Limited Warping Path Length - Université d'Angers Accéder directement au contenu
Article Dans Une Revue Information Sciences Année : 2017

Dynamic Time Warping Under Limited Warping Path Length

Résumé

Dynamic Time Warping (DTW) is probably the most popular distance measure for time series data, because it captures flexible similarities under time distortions. However, DTW has long been suffering from the pathological alignment problem, and most existing solu- tions, which essentially impose rigid constraints on the warping path, are likely to miss the correct alignments. A crucial observation on pathological alignment is that it always leads to an abnormally large number of links between two sequences. Based on this new ob- servation, we propose a novel variant of DTW called LDTW, which limits the total number of links during the optimization process of DTW. LDTW not only oppresses the patholog- ical alignment effectively, but also allows more flexibilities when measuring similarities. It is a softer constraint because we still let the optimization process of DTW decide how many links to allocate to each data point and where to put these links. In this paper, we introduce the motivation and algorithm of LDTW and we conduct a nearest neighbor clas- sification experiment on UCR time series archive to show its performance.
Fichier principal
Vignette du fichier
LDTW_author_version.pdf (4.57 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-01470554 , version 1 (28-02-2017)

Identifiants

Citer

Zheng Zhang, Romain Tavenard, Adeline Bailly, Xiaotong Tang, Ping Tang, et al.. Dynamic Time Warping Under Limited Warping Path Length. Information Sciences, 2017, 393, pp.91 - 107. ⟨10.1016/j.ins.2017.02.018⟩. ⟨hal-01470554⟩
1312 Consultations
4702 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More