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。
In the experiment, a mountain-climbing searching method and a curve-fitting method were employed to determine the integral pixel displacement and the sub-pixel displacement respectively.
实验中分别应用了爬山搜索法和相关系数拟合法来分别搜索整像素的位移和亚像素的位移。
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