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Time Series Pattern Recognition based on Branch and Bound Dynamic Time Warping  

Jang, Seok-Woo (안양대학교 디지털미디어학과)
Park, Young-Jae (숭실대학교 컴퓨터학부)
Kim, Gye-Young (숭실대학교 컴퓨터학부)
Publication Information
Journal of KIISE:Software and Applications / v.37, no.7, 2010 , pp. 584-589 More about this Journal
Abstract
The dynamic time warping algorithm generally used in time series pattern recognition spends most of the time in generating the correlation table, and it establishes the global path constraint to reduce the corresponding time complexity. However, the constraint restrains just in terms of the time axis, not considering the contents of input patterns. In this paper, we therefore propose an efficient branch and bound dynamic time warping algorithm which sets the global constraints by adaptively reflecting the patterns. The experimental results show that the proposed method outperforms conventional methods in terms of the speed and accuracy.
Keywords
Branch and Bound; Dynamic Time Warping; Time Series Data; Constraints;
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