混沌伪随机序列的谱熵复杂性分析

摘要

To analyze the complexity of chaotic pseudo-random sequences accurately, spectral entropy (SE) algorithm is used to analyze chaotic pseudo-random sequences generated by Logistic map, Gaussian map or TD-ERCS system. The SE algorithm has few parameters, and has high robustness with the sequence length N (the only parameter) and the pseudo-random binary number K . Using sliding window method, the evolution features are analyzed, and complexity of discrete chaotic systems with different initial conditions and system parameters are calculated. The results show that SE algorithm is effective for analyzing the complexity of the chaotic pseudorandom sequences, and TD-ERCS is a high complexity system with wide parameter range, and has the best complex performance among the three chaotic systems. The complexity of the same chaotic system with different initial values fluctuates within a small range. It provides a theoretical and experimental basis for the applications of chaotic sequences in the field of information security.%为了准确分析混沌伪随机序列的结构复杂性,采用谱熵算法对Logistic映射、Gaussian映射和TD-ERCS系统产生的混沌伪随机序列复杂度进行了分析.谱熵算法具有参数少、对序列长度N(惟一参数)和伪随机进制数K鲁棒性好的特点.采用窗口滑动法分析了混沌伪随机序列的复杂度演变特性,计算了离散混沌系统不同初值和不同系统参数条件下的复杂度.研究表明,谱熵算法能有效地分析混沌伪随机序列的结构复杂度；在这三个混沌系统中,TD-ERCS系统为广域高复杂度混沌系统,复杂度性能最好；不同窗口和不同初值条件下的混沌系统复杂度在较小范围内波动.为混沌序列在信息安全中的应用提供了理论和实验依据.