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In this paper, the authors discuss the application of Principal Component Analysis (PCA), for the purpose of determining a similarity/distance measure among multivariate time series. They review several PCA-based measures that have been proposed by researchers from diverse scientific fields and they extend the well-known statistic in the Statistical Process Control community, SPE, in order to define a novel distance measure. They conducted experiments on four datasets, which have been used extensively in the literature, and they provide the results of their performance with respect to classification accuracy.
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