Theoretic analysis and simulation indicate that the algorithm has better performance for sub-trend searching in temporal and space, and is useful in time series dynamic feature analysis.
理论分析和仿真结果表明，该算法对基于趋势表示的子序列搜索在时间和空间上都具有更优的性能，适用于时间序列的动态特征分析。
Theoretic analysis and simulation indicate that the algorithm has better performance for sub-trend searching in temporal and space, and is useful in time series dynamic feature analysis.
理论分析和仿真结果表明，该算法对基于趋势表示的子序列搜索在时间和空间上都具有更优的性能，适用于时间序列的动态特征分析。
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