Approximate analytical solutions for a class of nonlinear stochastic differential equations

被引:2
|
作者
Meimaris, A. T. [1 ]
Kougioumtzoglou, I. A. [2 ]
Pantelous, A. A. [1 ]
机构
[1] Monash Univ, Monash Business Sch, Dept Econometr & Business Stat, 20 Chancellors Walk, Clayton, Vic 3800, Australia
[2] Columbia Univ, Fu Fdn Sch Engn & Appl Sci, Dept Civil Engn & Engn Mech, 500 West 120th St, New York, NY 10027 USA
基金
美国国家科学基金会;
关键词
Stochastic Differential Equations; Stochastic Dynamics; Path Integral; Error quantification; Cauchy-Schwarz inequality; RESPONSE DETERMINATION;
D O I
10.1017/S0956792518000530
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
An approximate analytical solution is derived for a certain class of stochastic differential equations with constant diffusion, but nonlinear drift coefficients. Specifically, a closed form expression is derived for the response process transition probability density function (PDF) based on the concept of the Wiener path integral and on a Cauchy-Schwarz inequality treatment. This is done in conjunction with formulating and solving an error minimisation problem by relying on the associated Fokker-Planck equation operator. The developed technique, which requires minimal computational cost for the determination of the response process PDF, exhibits satisfactory accuracy and is capable of capturing the salient features of the PDF as demonstrated by comparisons with pertinent Monte Carlo simulation data. In addition to the mathematical merit of the approximate analytical solution, the derived PDF can be used also as a benchmark for assessing the accuracy of alternative, more computationally demanding, numerical solution techniques. Several examples are provided for assessing the reliability of the proposed approximation.
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页码:928 / 944
页数:17
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