Hypothesis Test-based Similarity Matching algorithm of time-series data

There were many deficiencies in traditional sequences distance and similarity matching algorithm dealing with multivariate time-series. The paper firstly expounded the definition of time-series, furthermore proposed a new distance measure aimed at multivariate time-series. Secondly it advanced the HTbSM (Hypothesis Test-based Similarity Matching algorithm of multivariate time-series data). The algorithm included two parts: Transform, Hypothesis Test. Finally, an experiment was conducted, showing that the algorithm could do well in the multivariate time-series, as it has advantage of effectiveness, simplicity, robustness, and controllability.