一种确定混沌伪随机序列复杂度的模糊关系熵测度

将模糊关系的概念引入混沌伪随机序列复杂度的测度方法之中,提出了一种新的混沌伪随机序列复杂度测度方法——模糊关系熵(fuzzy relationship entropy,简记为F-REn)测度方法,并推导了F-REn的两个基本性质.仿真结果表明,该测度方法能够有效测度混沌伪随机序列的复杂度,与近似熵(ApEn)测度方法和符号熵测度方法相比,F-REn测度具有更加好的对序列符号空间的适用性、更加小的对测量维度的敏感性和更加强的对分辨率参数的鲁棒性. 关键词： 混沌伪随机序列 模糊理论 复杂度

New complexity metric of chaotic pseudorandom sequences using fuzzy relationship entropy

A new complexity metric to evaluate the unpredictability of the chaotic pseudorandom sequences based on the fuzzy relationship entropy (F-REn) is proposed in the view of maximal randomness of the sequences with arbitrary length. On this condition,two basic properties of F-REn are proved. Simulations and analysis results show that, the proposed F-REn works effectively to discern the changing complexities of the chaotic pseudorandom sequences, and compared with complexity metric based on the approximate entropy(ApEn) and symbolic dynamics approach , F-REn works have obvious advantages in the applicability of symbolic space, the sensitivity of vector dimension and the robustness of resolution parameter.