Finding Discordant Subsequence in Multivariate Time Series
作者： Xiaoqing Weng , Junyi Shen
DOI: 10.1109/ICAL.2007.4338852
关键词:
摘要: Discordant subsequence in multivariate time series (MTS) is the that least similar to all other MTS subsequences. In this paper, an algorithm of finding discordant MTS, based on solving set, proposed. Subsequences can be extracted by use a sliding window. An extended Frobenius norm used compute distance between The complexity subquadratic length MTS. We conduct experiments two real-world datasets, stock market dataset and BCI (Brain Computer Interface) dataset. experiment results show efficiency effectiveness algorithm.
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