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具有 sigmoidal 恢复变量的离散 FitzHugh-Nagumo 神经元模型中的奇异非混沌动力学。

Strange nonchaotic dynamics in a discrete FitzHugh-Nagumo neuron model with sigmoidal recovery variable.

机构信息

Centre for Nonlinear Systems, Chennai Institute of Technology, Chennai 600069, India.

Department of Electronics and Communications Engineering, University Centre for Research and Development, Chandigarh University, Mohali-140413, Punjab.

出版信息

Chaos. 2022 Jul;32(7):073106. doi: 10.1063/5.0089373.

Abstract

We report the appearance of strange nonchaotic attractors in a discrete FitzHugh-Nagumo neuron model with discontinuous resetting. The well-known strange nonchaotic attractors appear in quasiperiodically forced continuous-time dynamical systems as well as in a discrete map with a small intensity of noise. Interestingly, we show that a discrete FitzHugh-Nagumo neuron model with a sigmoidal recovery variable and discontinuous resetting generates strange nonchaotic attractors without external force. These strange nonchaotic attractors occur as intermittency behavior (locally unstable behavior in laminar flow) in the periodic dynamics. We use various characterization techniques to validate the existence of strange nonchaotic attractors in the considered system.

摘要

我们报告了在具有不连续重置的离散 FitzHugh-Nagumo 神经元模型中出现的奇异非混沌吸引子。众所周知的奇异非混沌吸引子出现在准周期力连续时间动力系统以及具有小噪声强度的离散映射中。有趣的是,我们表明,具有 sigmoidal 恢复变量和不连续重置的离散 FitzHugh-Nagumo 神经元模型在没有外力的情况下产生奇异非混沌吸引子。这些奇异非混沌吸引子作为间歇行为(层流中的局部不稳定行为)出现在周期性动力学中。我们使用各种特征化技术来验证所考虑系统中奇异非混沌吸引子的存在。

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