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International Journal of Intelligent Systems and Applications(IJISA)

ISSN: 2074-904X (Print), ISSN: 2074-9058 (Online)

Published By: MECS Press

IJISA Vol.10, No.7, Jul. 2018

Clustering Matrix Sequences Based on the Iterative Dynamic Time Deformation Procedure

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Author(s)

Zhengbing Hu, Sergii V. Mashtalir, Oleksii K. Tyshchenko, Mykhailo I. Stolbovyi

Index Terms

Time Series;Segmentation;Clustering;Video Stream;Proximity Measure;Dynamic Time Warping

Abstract

The techniques of Dynamic Time Warping (DTW) have shown a great efficiency for clustering time series. On the other hand, it may lead to sufficiently high computational loads when it comes to processing long data sequences. For this reason, it may be appropriate to develop an iterative DTW procedure to be capable of shrinking time sequences. And later on, a clustering approach is proposed for the previously reduced data (by means of the iterative DTW). Experimental modeling tests were performed for proving its efficiency.

Cite This Paper

Zhengbing Hu, Sergii V. Mashtalir, Oleksii K. Tyshchenko, Mykhailo I. Stolbovyi, "Clustering Matrix Sequences Based on the Iterative Dynamic Time Deformation Procedure", International Journal of Intelligent Systems and Applications(IJISA), Vol.10, No.7, pp.66-73, 2018. DOI: 10.5815/ijisa.2018.07.07

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