小世界神经网络的二次超谐波随机共振

随机共振现象是非线性系统中普遍存在的自然现象.主要通过研究小世界生物神经网络中的输出信噪比与反映小世界效应的重连概率p、耦合强度c以及输入信号振幅A之间的关系，来揭示小世界生物神经网络的二次超谐波随机共振的一些规律.发现对于Hodgkin-Huxley小世界神经网络，并不是信号越强，信噪比越大，而是输入信号的振幅A存在一个最优值A_O，此时网络信噪比最大.

The second super-harmonic stochastic resonance in the neural networks with small-world character

Stochastic resonance is a common natural phenomenon in nonlinear systems. By studying the relations between the out put signal-to-noise ratio (SNR) of the biologic neural network with small-world character and the rewiring probability p which reflects the effect of small-world,the coupling strength c, amplitude A of input signal, we revealed some regularities of the second super-harmonic stochastic resonance in the biologic neural network, and found that the out put SNR doesn't monotonicly increase as the forcing amplitude A increases, but there exists an optimal value A_O for the Hodgkin-Huxley (HH) neural network with small-world character. The out put SNR reaches its maximum when A is equal to A_O.