摘要
研究了Lévy噪声和高斯白噪声共同激励下的一维FHN神经元系统的动力学特性。利用Janicki-Weron算法产生Lévy噪声,并采用四阶Runge-Kutta算法模拟出方程的稳态概率密度函数;然后通过稳态概率密度函数图像进一步对FHN神经元系统进行了稳态分析。通过数值仿真发现:乘性噪声强度D、加性噪声强度Q、稳定性指标α、偏斜参数β这些参数都可以诱导系统产生相变现象;乘性噪声强度D和稳定性指标α的增大使得FHN神经元系统停留在激发态的概率逐渐升高;加性噪声强度Q和偏斜参数β的增大使得神经元系统逐渐从激发态转变到静息态;乘性噪声强度D和加性噪声强度Q的改变对系统的作用正好相反。
In this paper,the dynamic characteristics in FHN neural system driven by Lévy noise and Gaussian white noise are studied.Lévy noise is generated by Janicki-Weron algorithm,and the stationary probability densities(SPD)functions of the system are obtained by using fourth-order Runge-Kutta method.Then the steady state analysis of the FHN neural system is carried out by the SPD figures.Results show that the intensity of multiplicative noise D,the intensity of additive noise Q,the stability indexαand the skewness parameterβcan induce phase transition.Moreover,the figures show that with the increase of the intensity of multiplicative noise D and stability indexα,the probability of retain exited state in FHN neural system gradually rising.But the increase of the intensity of additive noise Q and the skewness parameterβinduce it from excited state to resting state.The change of multiplicative noise intensity D and additive noise intensity Q has the opposite effect on the system.
作者
郭永峰
王琳杰
魏芳
Guo Yongfeng;Wang Linjie;Wei Fang(School of Mathematical Sciences,Tianjin Polytechnic University,300387,Tianjin,China)
出处
《应用力学学报》
CAS
CSCD
北大核心
2019年第4期806-811,994,共7页
Chinese Journal of Applied Mechanics
基金
国家自然科学基金(11672207)
天津市自然科学基金(17JCYBJC15700)
