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Exact variable-length anomaly detection algorithm for univariate and multivariate time series.

, , , and . Data Min. Knowl. Discov., 32 (6): 1806-1844 (2018)

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Observing Infinite-dimensional Dynamical Systems., and . SIAM J. Applied Dynamical Systems, 9 (4): 1229-1243 (2010)A Service Framework for Learning, Querying and Monitoring Multivariate Time Series., , and . ICEIS (2), page 92-101. SciTePress, (2011)Experiencing SAX: a novel symbolic representation of time series., , , and . Data Min. Knowl. Discov., 15 (2): 107-144 (2007)Analyzing Log Analysis: An Empirical Study of User Log Mining., , , , , and . LISA, page 53-68. USENIX Association, (2014)Mining Time Series Data., , , , , and . The Data Mining and Knowledge Discovery Handbook, Springer, (2005)Efficient Discovery of Unusual Patterns in Time Series., , , and . New Generation Comput., 25 (1): 61-93 (2006)Finding structurally different medical data., and . CBMS, page 1-8. IEEE Computer Society, (2009)R-Checkpoint Algorithm for Multi-Event Decision Making over Multivariate Time Series., , and . DSS, volume 238 of Frontiers in Artificial Intelligence and Applications, page 209-220. IOS Press, (2012)Using myoelectric signals to recognize grips and movements of the hand., , , , and . BIBM, page 388-394. IEEE Computer Society, (2015)Efficient discovery of time series motifs with large length range in million scale time series., and . ICDM, page 1213-1222. IEEE Computer Society, (2017)