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Mean-square stability of Euler method for nonlinear neutral stochastic delay differential equations

机译:非线性中立随机时滞微分方程的欧拉方法的均方稳定性

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Stochastic differential equations can always simulate the scientific problem in practical truthfully. They have been widely used in Physics, Chemistry, Cybernetics, Finance, Neural Networks, Bionomics, etc. So far there are not many results on the numerical stability of nonlinear neutral stochastic delay differential equations. The purpose of our work is to show that the Euler method applied to the nonlinear neutral stochastic delay differential equations is mean square stable under the condition which guarantees the stability of the analytical solution. The main aim of this paper is to establish new results on the numerical stability. It is proved that the Euler method is mean-square stable under suitable condition, i.e., assume the some conditions are satisfied, then, the Euler method applied to the nonlinear neutral stochastic delay differential equations with initial data is mean-square stable. Moreover, the theoretical result is also verified by a numerical example.
机译:随机微分方程始终可以如实地模拟科学问题。它们已被广泛用于物理,化学,控制论,金融,神经网络,生物组学等领域。到目前为止,非线性中立随机时滞微分方程的数值稳定性没有很多结果。我们的工作目的是证明,在保证解析解稳定的条件下,应用于非线性中立随机时滞微分方程的Euler方法是均方稳定的。本文的主要目的是建立数值稳定性的新结果。证明了在适当条件下,即在满足某些条件的情况下,欧拉方法是均方稳定的,然后,将带有初始数据的非线性中立随机时滞微分方程的欧拉方法是均方稳定的。此外,理论结果也通过数值示例得到了验证。

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