Boolean chaos generated by autonomous Boolean networks has been successfully applied to random number generation, physical unclonable function, gene regulation and reservoir computing, because it can generate complex dynamics with very simple structure. Influences of noise on autonomous Boolean networks chaotic system in delay time parameter spaces are analyzed by simulation and experiments in this article. It is found that the influences of noise on Boolean chaotic system is two-sided. What is new is that noise may lead to chaos instability, i.e., the noise transforms the original chaotic outputs into periodic outputs, which means the Boolean chaos lacks robustness to noise. Then like other chaotic systems noise contributes to Boolean chaotic unpredictability. The physical origin of noise induced Boolean chaos instability is analyzed that noise may easily change delay time parameter no longer a chaotic parameter in discontinuous chaotic parameter spaces. In addition, simulation and experiments on FPGA show that the increase of the number of nonlinear elements of the chaotic system can improve the Boolean chaos robustness to noise. This research is significant to the design of autonomous Boolean networks.

由自治布尔网络生成的布尔混沌已成功应用于随机数生成、物理不可克隆函数、基因调控和储层计算，因为它可以以非常简单的结构生成复杂的动力学。本文通过仿真和实验分析了噪声对延迟时间参数空间中的自治布尔网络混沌系统的影响。发现噪声对布尔混沌系统的影响是两方面的。新的是噪声可能导致混沌不稳定，即噪声将原始混沌输出转换为周期输出，这意味着布尔混沌缺乏对噪声的鲁棒性。然后像其他混沌系统一样，噪声会导致布尔混沌不可预测性。分析了噪声引起布尔混沌不稳定性的物理根源，噪声很容易改变延迟时间参数，在不连续混沌参数空间中不再是混沌参数。此外，在FPGA上的仿真和实验表明，增加混沌系统非线性元素的数量可以提高布尔混沌对噪声的鲁棒性。这项研究对自主布尔网络的设计具有重要意义。