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On the Link between Strongly Connected Iteration Graphs and Chaotic Boolean Discrete-Time Dynamical Systems

机译:关于强连通迭代图与混沌布尔离散时间动力系统之间的联系

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摘要

Chaotic functions are characterized by sensitivity to initial conditions, transitivity, and regularity. Providing new functions with such properties is a real challenge. This work shows that one can associate with any Boolean network a continuous function, whose discrete-time iterations are chaotic if and only if the iteration graph of the Boolean network is strongly connected. Then, sufficient conditions for this strong connectivity are expressed on the interaction graph of this network, leading to a constructive method of chaotic function computation. The whole approach is evaluated in the chaos-based pseudo-random number generation context.
机译:混沌函数的特征是对初始条件,传递性和规则性敏感。提供具有此类属性的新功能是一个真正的挑战。这项工作表明,可以与任何布尔网络关联一个连续函数,当且仅当布尔网络的迭代图紧密相连时,其离散时间迭代才是混沌的。然后,在该网络的交互图上表达了用于这种强连通性的充分条件,从而导致了一种构造混沌函数的方法。在基于混沌的伪随机数生成上下文中评估整个方法。

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