样本熵是一种有别于近似熵的不计数自身匹配的统计量，是对于近似熵算法的改进。样本熵与近似熵的物理意义一样，表示非线性动力学系统产生新模式概率的大小，主要用来定量刻画系统的规则度及复杂度。样本熵值越低，序列自我相似性越高，产生新模式的概率越低，时间序列越简单；反之，样本熵值越大，序列自我相似性越低，产生新模式的概率越高，时间序列越复杂。样本熵计算用程序VB6.0语言实现。-Sample entropy　is different from the research and development of a self-similar entropy does not match the count statistic, approximate entropy algorithm for improvement. Sample entropy and approximate entropy of the physical meaning of the same, that a new model of nonlinear dynamical system to produce the probability of the size of the system is mainly used to quantitatively characterize the degree and complexity of the rules. Sample entropy value is lower, the higher the sequence similarity of self-produce the new model, the lower the probability, the more simple time series　the other hand, the larger the sample entropy, sequence similarity, the lower self, the higher the probability of generating new models, the time more complex sequences. Sample entropy calculation procedures VB6.0 language.