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STOCHASTIC DYNAMICS OF THE FITZHUGH-NAGUMO NEURON MODEL THROUGH A MODIFIED VAN DER POL EQUATION WITH FRACTIONAL-ORDER TERM AND GAUSSIAN WHITE NOISE EXCITATION

机译:具有分数阶术语和高斯白噪声激发的改进范德波尔极方程的Fitzhugh-Nagumo神经元模型的随机动力学

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摘要

The stochastic response of the FitzHugh-Nagumo model is addressed using a modified Van der Pol (VDP) equation with fractional-order derivative and Gaussian white noise excitation. Via the generalized harmonic balance method, the term related to fractional derivative is splitted into the equivalent quasi-linear dissipative force and quasi-linear restoring force, leading to an equivalent VDP equation without fractional derivative. The analytical solutions for the equivalent stochastic equation are then investigated through the stochastic averaging method. This is thereafter compared to numerical solutions, where the stationary probability density function (PDF) of amplitude and joint PDF of displacement and velocity are used to characterized the dynamical behaviors of the system. A satisfactory agreement is found between the two approaches, which confirms the accuracy of the used analytical method. It is also found that changing the fractional-order parameter and the intensity of the Gaussian white noise induces P-bifurcation.
机译:使用具有分数级衍生物和高斯白噪声激发的改进的范德波(VDP)方程来解决Fitzhugh-Nagumo模型的随机响应。通过广义谐波平衡方法,与分数衍生物有关的术语分离成等效的准线性耗散力和准线性恢复力,导致不具有分数衍生物的等效VDP方程。然后通过随机平均方法研究了等效随机方程的分析解。此后与数值解决方案相比,其中振幅和速度的振幅和关节PDF的静止概率密度函数(PDF)用于表征系统的动力学行为。两种方法之间发现了令人满意的协议,这证实了使用的分析方法的准确性。还发现,改变分数阶参数和高斯白噪声的强度引起p分频。

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