Stochastic resonance and stability for a stochastic metapopulation system subjected to non-Gaussian noise and multiplicative periodic signal
Stochastic resonance and stability for a stochastic metapopulation system subjected to non-Gaussian noise and multiplicative periodic signal
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DOI：
10.1088/0031-8949/90/8/085002
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发表时间：
2015-08
期刊：
影响因子：
2.9
通讯作者：
Kang-Kang Wang-Kang;Xianbin Liu;Zhou Yu
中科院分区：
文献类型：
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作者：
Kang-Kang Wang-Kang;Xianbin Liu;Zhou Yu
研究了由加性高斯噪声、乘性非高斯噪声和噪声相关时间驱动的元种群系统的乘性周期信号引起的稳定性和随机共振现象。利用快速下降法、统一彩色噪声近似和McNamara和Wiesenfeld的SR理论，导出了绝热极限下平稳概率分布函数和信噪比的解析表达式。通过数值计算，分别讨论了增益噪声强度、乘法噪声强度和相关时间对稳态概率分布函数和信噪比的影响。结果表明，乘性噪声、加性噪声和偏离高斯噪声的参数都会破坏种群系统的稳定性。然而，噪声相关时间可以巩固系统的稳定性。另一方面，相关时间在激发信噪比和提高信噪比方面一直起着重要作用。在系统的不同参数条件下，乘性噪声、加性噪声和偏离参数既能激发SR现象，又能抑制SR现象，说明了不同噪声对非线性系统的影响的复杂性。
In this paper, the stability and stochastic resonance (SR) phenomenon induced by the multiplicative periodic signal for a metapopulation system driven by the additive Gaussian noise, multiplicative non-Gaussian noise and noise correlation time is investigated. By using the fast descent method, unified colored noise approximation and McNamara and Wiesenfeld’s SR theory, the analytical expressions of the stationary probability distribution function and signal-to-noise ratio (SNR) are derived in the adiabatic limit. Via numerical calculations, each effect of the addictive noise intensity, the multiplicative noise intensity and the correlation time upon the steady state probability distribution function and the SNR is discussed, respectively. It is shown that multiplicative, additive noises and the departure parameter from the Gaussian noise can all destroy the stability of the population system. However, the noise correlation time can consolidate the stability of the system. On the other hand, the correlation time always plays an important role in motivating the SR and enhancing the SNR. Under different parameter conditions of the system, the multiplicative, additive noises and the departure parameter can not only excite SR phenomenon, but also restrain the SR phenomenon, which demonstrates the complexity of different noises upon the nonlinear system.