An Effective Algorithm to Match Similar Time Series Pattern

This paper proposes an effective time series matching method by combining the empirical mode decomposition （EMD） with the alternative covering algorithm.It decomposes at first a time series into a trend part and some detail parts using the EMD,and then divides all trend series into two sets：training sets and testing sets.Each pattern is learnt during the training process,and the trend series in the testing set are assigned to one of the labeled patterns based on its distance to the center of each covering.Experimental results show that the proposed method performs well and appears to be more suitable for high-dimensionality matching.