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| DTW Based Pattern Matching Method for Multivariate Time Series |
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Abstract Existing methods for matching multivariate time series can not measure similarity efficiently and accurately at the same time. Multivariate time series are fitted with multidimensional piecewise method. The angle of inclination and time span of a fitting line segment are chosen as feature pattern, and then a pattern matching method based on DTW for multivariate time series is proposed. Finally, its validity is testified by experiments. The experimental results show that the similarity of multivariate time series are measured efficiently and accurately by the proposed method, especially for series which present a whole process in a comparatively long time.
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2011, Vol. 24 
