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The parametrix method approach to diffusions in a turbulent Gaussian environment

机译:湍流高斯环境中扩散的参数化方法

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In this paper we deal with the solutions of Ito stochastic differential equation dX(epsilon)(t) = 1/epsilon V (t/epsilon(2), X-epsilon(t)/epsilon(alpha)) dt + root 2 dB(t), for a small parameter epsilon. We prove that for 0 less than or equal to alpha < 1 and V a divergence-free, Gaussian random field, sufficiently strongly mixing in t variable the family of processes {X-epsilon(t)}(t greater than or equal to 0), epsilon > 0 converges weakly to a Brownian motion. The entries of the covariance matrix of the limiting Brownian motion are given by a(i,j) = 2 delta(i,j) + integral(-infinity)(+infinity) R-i,R-j(t, 0) dt, i, i = 1,..., d, where [R-i,R-j(t,x)] is the covariance matrix of the field V. To obtain this result we apply a version of the parametrix method for a linear parabolic PDE (see Friedman, 1963). (C) 1998 Elsevier Science B.V. All rights reserved. [References: 14]
机译:在本文中,我们处理的是伊藤随机微分方程dX(epsilon)(t)= 1 / epsilon V(t / epsilon(2),X-epsilon(t)/ epsilon(alpha)dt +根2 dB的解。 (t),用于小参数ε。我们证明,对于0小于或等于alpha <1且V为无散度的高斯随机场,在t变量中充分强烈地混合了一系列过程{X-epsilon(t)}(t大于或等于0 ),epsilon> 0弱收敛至布朗运动。极限布朗运动的协方差矩阵的项由a(i,j)= 2 delta(i,j)+积分(-无穷大)(+无穷大)Ri,Rj(t,0)dt,i,给出i = 1,...,d,其中[Ri,Rj(t,x)]是字段V的协方差矩阵。为获得此结果,我们对线性抛物线PDE应用了parametrix方法的一种形式(请参见Friedman (1963年)。 (C)1998 Elsevier Science B.V.保留所有权利。 [参考:14]

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