Research on the stability of complexity of chaos-based pseudorandom sequence
混沌伪随机序列的复杂度的稳定性研究

Intensive statistical complexity can reflect the random nature of chaos-based pseudorandom sequence. Based on this property, the definition of k-error intensive statistical complexity is presented and two basic properties of it are proved in this paper, which can be used to measure the stability of complexity of chaos-based pseudorandom sequences. Based on chaos-based pseudorandom sequences produced via Logistic, Henon, Cubic, Chebyshev and Tent maps, an example is given to demonstrate how it works. Simulation results indicate that the approach is effective, it can distinguish the stability of diverse chaos-based pseudorandom sequences, and is an effective way for evaluating the stability of chaos-based sequences.