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机构地区:[1]广东技术师范学院电子与信息学院,广州510665 [2]华南理工大学电子与信息学院,广州510640
出 处:《计算机应用》2009年第9期2548-2549,2553,共3页journal of Computer Applications
基 金:国家自然科学基金资助项目(60802004);广东省科技厅科技计划项目(2007B010200041)
摘 要:采用符号熵分析法,分析和讨论了经典的Logistic映射和Henon映射的类随机性强弱。先将离散混沌系统产生的实数序列转化为二进制序列,然后进行编码,计算其符号熵,绘制其符号熵图,并深入讨论了系统参数和初始值对符号熵的影响。数值仿真分析表明,符号熵法能定量区别不同离散混沌系统类随机性的强弱。同时作为随机源,Logistic映射比Henon映射好。Random-like properties of typical Logistic map and Henon map were analyzed and discussed by using symbol entropy algorithm. Firstly, the binary sequences were obtained from real-valued sequences generated by discrete chaotic maps, then were coded. Symbol entropies of the binary sequences were calculated and their curves were plotted. Influences of system parameter and initial value on symbol entropy were discussed. Simulation results show that symbol entropy algorithm can be used to statistically identify the strength of random-like properties of discrete chaotic maps, and Logistic map is better than Henon map as the source of randomness.
关 键 词:混沌 类随机性 符号熵 LOGISTIC映射 HENON映射
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