基于原生熵的Logistic映射复杂性分析

On the complexity of Logistic map based on primitive entropy

在序列原生生成过程的基础上,提出了原生熵的概念来分析离散混沌映射的复杂性。先对实值混沌映射量化成二值混沌序列,然后计算其原生熵的大小,并以Logistic映射为例证明了此算法的有效性。仿真结果表明此方法能反映离散混沌系统的随机本质,可用于准确度量离散混沌系统的复杂性强弱,且计算简单。

The notion of primitive entropy is proposed, which is based on primitive production process of a sequence, to measure the complexity of discrete chaotic maps. Real chaotic map is firstly quantified into binary chaotic sequence, and then its primitive entropy is ebtained. As an example, Logistic map is given to indicate that the algorithm is effective. Simulation results show that the approach can describe the random essence of discrete chaotic system and can be used to measure the complexity of discrete chaotic maps with simple computation.