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噪声广泛存在于生物神经系统中,对系统功能具有重要作用.采用神经元二维映射模型构建一个复杂神经网络,由多个小世界子网络构成,研究了Gaussian白噪声诱导的随机共振现象.研究发现,只有合适的噪声强度才能使神经网络对输入刺激信号的频率响应达到峰值.另外,网络结构对系统随机共振特性有重要影响.在固定的耦合强度下,存在一个最优的局部小世界子网络结构,使得整个系统的频率响应最佳.
Noise exists widely in the biological nervous system, and plays an important role in the system function.Using the two-dimensional neuron mapping model to construct a complex neural network composed of many small-world sub-networks, the phenomenon of stochastic resonance induced by Gaussian white noise is studied. It is found that only the proper noise intensity can make the neural network reach the peak value of the frequency response of the input stimulus signal.In addition, the network structure has an important influence on the stochastic resonance characteristics of the system.At a fixed coupling strength, there exists an optimal local small world sub-region Network structure, making the best frequency response of the entire system.