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Stochastic averaging for a class of single degree of freedom systems with combined Gaussian noises

机译:一类具有组合高斯噪声的单自由度系统的随机平均

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摘要

We develop the stochastic averaging method to investigate the asymptotic stationary solution and the stochastic bifurcations of a class of single degree of freedom system with combined Gaussian white and colored noises, and to derive the Fokker–Planck–Kolmogorov (FPK) equations. The general stationary solutions will be obtained analytically under some suitable conditions. Theoretically, a general algebraic expression of the stationary probability density function of amplitude for the dynamical system is presented to consider the influences of correlation time of the noise and the noise intensity on stochastic bifurcations. Then, an example is given to illustrate the averaging method, and the effectiveness of the averaging method is verified via comparing the analytical results with those from Monte Carlo simulation. Finally, stochastic bifurcations are discussed through a qualitative change of the stationary probability distribution. It indicates that system parameters, noise intensity, and noise correlation time can be treated as bifurcation parameters, respectively.
机译:我们开发了一种随机平均方法来研究一类具有高斯白噪声和彩色噪声的单自由度系统的渐近平稳解和随机分叉,并推导了Fokker-Planck-Kolmogorov(FPK)方程。一般的固定溶液将在某些合适的条件下通过分析获得。从理论上讲,提出了动力系统幅值平稳概率密度函数的一般代数表达式,以考虑噪声相关时间和噪声强度对随机分叉的影响。然后,给出一个例子来说明平均方法,并通过将分析结果与蒙特卡洛模拟的结果进行比较,验证了平均方法的有效性。最后,通过平稳概率分布的质变讨论了随机分支。它表明系统参数,噪声强度和噪声相关时间可以分别视为分叉参数。

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