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研究了非高斯噪声激励下含周期信号的FHN模型的动力学行为.通过计算神经元的平均响应时间、观察神经元的共振活化和噪声增强稳定现象,分析了非高斯噪声对神经元动力学行为的影响.发现通过改变非高斯噪声的相关时间可以有效地改变共振活化和噪声增强稳定现象.观察到在强相关噪声下不同强度的非高斯噪声抑制了神经元的噪声增强稳定现象而共振活化现象几乎不变,也就是非高斯噪声有效地增强了神经响应的效率.观察了平均响应时间与非高斯噪声参数q之间的关系,当q为一个有限的小于1的值时,平均响应时间取得最小值.最后表明在一定条件下,非高斯噪声出现重尺度现象,即非高斯噪声产生的效果可以由高斯白噪声来估计.
The dynamical behavior of FHN model with periodic signal stimulated by non-Gaussian noise was studied. By calculating the average response time of neurons and observing the resonance activation and the noise-enhanced stabilization of neurons, the effects of non-Gaussian noise on neuronal dynamics It is found that the resonance activation and noise enhancement can be effectively changed by changing the correlation time of non-Gaussian noise.Non-Gaussian noise of different intensities under strong correlated noise is observed to suppress the neuronal noise enhancement and stabilization while the resonance activation Almost unchanged, that is, non-Gaussian noise effectively enhances the efficiency of the neural response.We observe the relationship between the average response time and the non-Gaussian noise parameter q, and when q is a finite value less than 1, the average response time is obtained Finally, it shows that under certain conditions, non-Gaussian noise appears heavy scale phenomenon, that is, the effect of non-Gaussian noise can be estimated by Gaussian white noise.