In this paper, the dynamical complexity of FHN neuron system under the co-excitation of correlated noises and periodic signals is studied by means of information theory measures. Based on the definition of statistical complexity and normalized Shannon entropy, as well as the Bandt–Pompe algorithm, the total statistical complexity and the total normalized Shannon entropy of the FHN neuron system are calculated. Because the potential function of the system is asymmetric, we also calculate the statistical complexity and the normalized Shannon entropy in two different potential wells respectively. Moreover, the effects of additive noise intensity, multiplicative noise intensity, noise correlation time, cross-correlation strength and amplitude on dynamical complexity are analyzed.

中文翻译：

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相关噪声和周期信号驱动的 FHN 神经元系统的动态复杂性

本文采用信息论方法研究了相关噪声和周期信号共激励下FHN神经元系统的动力学复杂性。基于统计复杂度和归一化香农熵的定义，以及Bandt-Pompe算法，计算了FHN神经元系统的总统计复杂度和总归一化香农熵。由于系统的势函数是不对称的，我们还分别计算了两个不同势阱中的统计复杂度和归一化香农熵。此外，分析了加性噪声强度、乘性噪声强度、噪声相关时间、互相关强度和幅度对动态复杂度的影响。