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Clustering matrix sequences based on the iterative dynamic time deformation procedure

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成果类型:
期刊论文
作者:
Zhengbing Hu;Sergii V. Mashtalir;Oleksii K. Tyshchenko;Mykhailo I. Stolbovyi
作者机构:
School of Educational Information Technology, Central China Normal University, Wuhan, China
Kharkiv National University of Radio Electronics, Kharkiv, Ukraine
Institute for Research and Applications of Fuzzy Modeling, CE IT4Innovations, University of Ostrava, Ostrava, Czech Republic
语种:
英文
关键词:
Clustering;Dynamic Time Warping;Proximity Measure;Segmentation;Time Series;Video Stream
期刊:
International Journal of Intelligent Systems and Applications
ISSN:
2074-9058
年:
2018
卷:
10
期:
7
页码:
66-73
基金类别:
This scientific work was financially supported by self-determined research funds of CCNU from the colleges’ basic research and operation of MOE (CCNU16A02015). The third author also acknowledges the support of the Visegrad Scholarship Program—EaP #51700967 funded by the International Visegrad Fund (IVF).
机构署名:
本校为第一机构
院系归属:
教育信息技术学院
摘要:
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 te...

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