0, and initial condition, x(tau )(t) = g(t), -tau <= t <= 0, by assuming t'/> Applying the random variable transformation method to solve a class of random linear differential equation with discrete delay
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Applying the random variable transformation method to solve a class of random linear differential equation with discrete delay

机译:应用随机可变变换方法求解一类分立延迟的随机线性微分方程

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摘要

We randomize the following class of linear differential equations with delay, x(tau)' (t) = ax(tau) (t) bx(tau) (t -tau), t> 0, and initial condition, x(tau )(t) = g(t), -tau <= t <= 0, by assuming that coefficients a and b are random variables and the initial condition g(t) is a stochastic process. We consider two cases, depending on the functional form of the stochastic process g(t), and then we solve, from a probabilistic point of view, both random initial value problems by determining explicit expressions to the first probability density function, f(x, t; tau), of the corresponding solution stochastic processes. Afterwards, we establish sufficient conditions on the involved random input parameters in order to guarantee that f(x, t; tau) con- verges, as tau -> 0(+), to the first probability density function, say f(x, t), of the corresponding associated random linear problem without delay (tau = 0). The paper concludes with several numerical experiments illustrating our theoretical findings. (C) 2019 Published by Elsevier Inc.
机译:我们随着延迟,x(tau)'(t)= x(t)(t)bx(t-t-tau),t> 0和初始条件,x(tau),随机化以下类的线性微分方程。 (t)= g(t), - 通过假设系数a和b是随机变量,并且初始条件g(t)是随机过程。我们考虑两种情况,取决于随机过程G(t)的功能形式,然后我们通过确定对第一概率密度函数f(x相应的解决方案随机过程的T; TAU)。之后,我们在涉及的随机输入参数上建立充分条件,以保证F(x,t; tau),如tau - > 0(+),如第一个概率密度函数表示f(x, t),相应相关的随机线性问题而没有延迟(tau = 0)。本文的结论是若干数值实验,说明了我们的理论发现。 (c)2019由elsevier公司出版

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