摘要
分析了某种新型均匀分布伪随机数发生器对初始值要求严格的主要原因,并通过引入Logistic混沌映射,提出了能够消除不良初始值的改进伪随机数发生器。计算机仿真结果表明,该方法产生的均匀分布伪随机数对初始值选择无特殊要求,而且具有良好的统计性能。
One novel uniformly distributed pseudorandom number generator （PRNG） is proposed by using one-dimensional chaotic map with infinite collapses. However, it must be initialized by specific values. The pseudorandom sequences cannot be generated. Therefore, the main reasons for PRNG being sensitive to the initial values are analyzed, and an improved PRNG is proposed by incorporating the logistic chaotic map into eliminate error seeds. Simulation results show that the proposed method has no specific limitation on choices of initial values, and the generated sequences have good statistics performances.
出处
《数据采集与处理》
CSCD
北大核心
2006年第B12期6-10,共5页
Journal of Data Acquisition and Processing
基金
国家自然科学基金(60402013)资助项目。
关键词
混沌映射
伪随机数发生器
均匀分布
统计检验
chaotic map
pseudorandom number generator
uniform distribution
statistical test
