论文中利用信息熵、条件熵公式推导出先验知识度划分标准公式，该公式把信息熵公式中加权和转换为加权和加先验知识度参数。
The formula of the prior knowledge classification standard was deduced used of the information entropy and the condition entropy formula, which add the priori knowledge parameter to the weighting sum.
分析了已有的序列线性复杂度分析方法，提出了用近似熵算法计算混沌运动的测度熵，作为衡量混沌伪随机序列复杂度的标准。
In this paper, the conventional pseudo-random sequence linear complexity is discussed, and a new criterion is proposed, based on the approximate entropy.
分析了已有的序列线性复杂度分析方法，提出了用近似熵算法计算混沌运动的测度熵，作为衡量混沌伪随机序列复杂度的标准。
In this paper, the conventional pseudo-random sequence linear complexity is discussed, and a new criterion is proposed, based on the approximate entropy.
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