给出了序贯相似性检测算法中，自适应门限的选择方法。
Also a method of selecting an adaptive threshold in SSDA is given.
在实验中，与传统的序贯相似性检测算法(SSDA)作了比较，证明了本文算法的有效性。
In our experiment, it is proved to be effective after comparing with the conventional sequential similarity detection algorithm (SSDA).
在实验中，与传统的序贯相似性检测算法(SSDA)作了比较，证明了本文算法的有效性。
In our experiment, it is proved to be effective after comparing with the conventional sequential similarity detection algorithm (SSDA).
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