Adams methods for the efficient solution of stochastic differential equations with additive noise

被引：0

作者：

G. Denk

S. Schäffler

机构：

[1] Siemens AG ZT AN2,Institut für Angewandte Mathematik und Statistik

[2] Technische Universität München,undefined

来源：

Computing | 1997年 / 59卷

关键词：

65L05; 65L06; 65U05; 60H20; Stochastic differential equation; additive noise; strong solutions; Adams methods; numerical simulation; order of convergence; predictor-corrector scheme; random number; circuit simulation;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

The application of Adams methods for the numerical solution of stochastic differential equations is considered. Especially we discuss the path-wise (strong) solutions of stochastic differential equations with additive noise and their numerical computation. The special structure of these problems suggests the application of Adams methods, which are used for deterministic differential equations very successfully. Applications to circuit simulation are presented.

引用

页码：153 / 161

页数：8

共 50 条

[31] Weak convergence analysis of the linear implicit Euler method for semilinear stochastic partial differential equations with additive noise
Wang, Xiaojie
Gan, Siqing
JOURNAL OF MATHEMATICAL ANALYSIS AND APPLICATIONS, 2013, 398 (01) : 151 - 169
[32] Highly efficient difference methods for stochastic space fractional wave equation driven by additive and multiplicative noise
Zhou, Yanjiao
Xie, Jianqiang
Zhang, Zhiyue
APPLIED MATHEMATICS LETTERS, 2021, 116
[33] Accelerating numerical solution of stochastic differential equations with CUDA
Januszewski, M.
Kostur, M.
COMPUTER PHYSICS COMMUNICATIONS, 2010, 181 (01) : 183 - 188
[34] Numerical solution of stochastic differential-algebraic equations with applications to transient noise simulation of microelectronic circuits
Schein, O
Denk, G
JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS, 1998, 100 (01) : 77 - 92
[35] Random Attractor for Stochastic Hindmarsh-Rose Equations with Additive Noise
Phan, Chi
You, Yuncheng
JOURNAL OF DYNAMICS AND DIFFERENTIAL EQUATIONS, 2021, 33 (01) : 489 - 510
[36] Optimal error estimates of Galerkin finite element methods for stochastic partial differential equations with multiplicative noise
Kruse, Raphael
IMA JOURNAL OF NUMERICAL ANALYSIS, 2014, 34 (01) : 217 - 251
[37] Projection methods for stochastic differential equations with conserved quantities
Zhou, Weien
Zhang, Liying
Hong, Jialin
Song, Songhe
BIT NUMERICAL MATHEMATICS, 2016, 56 (04) : 1497 - 1518
[38] A STABLE NUMERICAL SCHEME FOR STOCHASTIC DIFFERENTIAL EQUATIONS WITH MULTIPLICATIVE NOISE
Mora, C. M.
Mardones, H. A.
Jimenez, J. C.
Selva, M.
Biscay, R.
SIAM JOURNAL ON NUMERICAL ANALYSIS, 2017, 55 (04) : 1614 - 1649
[39] PC analysis of stochastic differential equations driven by Wiener noise
Le Maitre, O. P.
Knio, O. M.
RELIABILITY ENGINEERING & SYSTEM SAFETY, 2015, 135 : 107 - 124
[40] ASYMPTOTIC STABILITY OF STOCHASTIC DIFFERENTIAL EQUATIONS DRIVEN BY LEVY NOISE
Applebaum, David
Siakalli, Michailina
JOURNAL OF APPLIED PROBABILITY, 2009, 46 (04) : 1116 - 1129

← 1 2 3 4 5 →