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以上来源于: WordNet
Thresholds are determined by dynamic time warping (DTW) distance between training sequences and standard model.
然后计算训练序列与标准步态模型之间的动态时间规整距离,确定阈值。
The audio signal feature, in this scheme, is the LPC Mel Cepstrum Coefficient (LPCMCC) and recognition algorithm is Dynamic Time Warping (DTW).
系统提取的音频信号特征为线性预测美尔倒谱系数(LPCMCC),采用动态时间规整(DTW)的识别算法。
The paper proposes an online handwriting signature verification algorithm with signature energy as feature based on dynamic time warping (DTW).
提出了一种基于DTW匹配的以签名能量为特征的在线手写签名验证算法。
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