APP下载

中立型随机延迟微分方程θ-方法的均方稳定性*

2014-09-05王文强

关键词:均方湘潭结论

王文强

(湘潭大学数学与计算科学学院,湖南 湘潭 411105)

中立型随机延迟微分方程θ-方法的均方稳定性*

王文强

(湘潭大学数学与计算科学学院,湖南 湘潭 411105)

讨论θ-方法用于求解非线性中立型随机延迟微分方程初值问题时数值解的稳定性,给出了θ-方法均方稳定的一个充分条件.

中立型随机延迟微分方程;θ-方法;均方稳定

随机延迟微分方程数值方法的稳定性研究是一件很有意义的工作,近年来已经开始受到越来越多的学者关注,相关的研究成果逐渐多起来.文献[1]提出了随机延迟微分方程Milstein方法.文献[2]建立了数值方法的均方稳定性(MS-稳定性)概念,证明了当线性标量系统的真解是均方稳定时,Euler-Maruyama方法的数值解是MS-稳定的.文献[3]研究了带有延迟项的随机微分方程半隐式Milstein数值方法的稳定性,通过对数值方法应用到线性试验方程上得到的差分方程进行讨论,给出了半隐式Milstein方法MS-稳定与GMS-稳定的条件.文献[4]运用Halanay-type理论,对常系数线性随机延迟微分方程给出了Euler-Maruyama方法均方稳定的判别准则.文献[5]研究了一类带有延迟项的线性随机延迟微分方程Milstein数值方法的稳定性,通过对数值方法应用到线性试验方程上得到的差分方程进行讨论,给出了Milstein方法MS-稳定的条件.文献[6]研究了改进的Milstein方法在有限区间上对随机延迟微分方程的分片近似的相关结论.文献[7-12]研究了随机延迟微分方程不同数值方法的均方稳定性与收敛性.文献[13]研究了中立型非线性随机延迟微分方程单步方法的均方收敛性.文献[14]进一步研究了中立型非线性随机延迟微分方程半隐式Euler方法的均方稳定性.

笔者主要讨论非线性中立型随机延迟微分方程初值问题,给出了θ-方法均方稳定的一个充分条件.

1 中立型随机延迟微分方程

设(Ω,F,{Ft}t≥0,P)是完备的概率空间,滤子{Ft}t≥0满足通常条件,即它们是右连续的且每一个Ft都包含所有的零概率集.考虑下列中立型随机延迟微分方程初值问题:

其中:实常数τ>0;W(t)是一维标准Wiener过程;初始函数φ是Hölder连续的,即存在常数γ>0,L>0,使当t,s∈[-τ,0]时,有E(|φ(t)-φ(s)|p)≤L|t-s|pγ,p=1,2;映射f:[0,+∞)×R×R→R和g:[0,+∞)×R×R→R充分光滑且满足

(2)

其中L,K1,K2均为常数,x∨y=max(x,y),且存在常数λ∈(0,1),对任意x,y1,y2∈R,有|N(y1)-N(y2)|≤λ|y1-y2|,

|N(x)|≤λ|x|.

(3)

此时方程(1)存在唯一强解X(t).

2 θ-方法的均方稳定性

将θ-方法用于数值求解初值问题(1),得到

Xk+1-N(Xk+1-m)=Xk-N(Xk-m)+(θf(tk+1,Xk+1,Xk+1-m)+(1-θ)f(tk,Xk,Xk-m))h+

g(tk,Xk,Xk-m)ΔWk2∈k=0,1,2,....

(4)

引理1 用θ-方法求解初值问题(1)所得的数值解{Xk}满足下列不等式:

证明由Yk=Xk-N(Xk-m)和(3)式,可得

|Xk|=|Yk+N(Xk-m)|≤|Yk|+|N(Xk-m)|≤|Yk|+λ|Xk-m|.

(5)

同理可得

(6)

将(6)式代入(5)式,有

|Xk|≤|Yk|+λ|Yk-m|+λ2|Yk-2m|+...+λc(k)|Yk-c(k)m|+λc(k)+1|Xk-c(k)m-m|.

(7)

(7)式两边平方,利用Cauchy不等式得

(8)

(8)式两边取数学期望,并注意到当l≤0时,有Xl=φ(lh),则引理1的结论得证.

作为一种特殊情形,根据文献[15]中推论6.8容易得到下面的结论:

定理1 如果方程(1a)满足下列条件:

(ⅰ) 存在2个正数λ1,λ2,使得对任意的x,y∈R,有

2(x-N(y))f(t,x,y)+g2(t,x,y)≤-λ1|x-N(y)|2+λ2y2;

那么方程(1)的零解是均方渐近稳定的.

将定理1稍加修改,可以得到下面的结论:

引理2 如果方程(1a)满足下列条件:

(ⅰ) 存在2个常数μ1>0,μ2≥0,使得对任意的x,y∈R,有

2(x-N(y))f(t,x,y)≤-μ1|x-N(y)|2+μ2y2;

(9)

(ⅱ)

(10)

那么方程(1)的零解是均方渐近稳定的.

证明根据三角不等式知|x|2=|x-N(y)+N(y)|2≤(|x-N(y)|+|N(y)|)2≤(|x-N(y)|+λ|y|)2.根据Cauchy不等式知

|x|2≤(|x-N(y)|+λ|y|)2≤(1+λ2)(|x-N(y)|2+|y|2).

(11)

因此联立(2),(9),(11)式可得

2(x-N(y))f(t,x,y)+g2(t,x,y)≤ -(μ1-(1+λ2)K2)|x-N(y)|2+

(μ2+(1+λ2)K2)y2.

(12)

根据定理1联立(10)和(12)式即知结论成立.

(13)

(14)

-7x2(1+x)+4x4(2x-1)<0,

(15)

下面给出关于数值方法稳定性分析的结论.首先记

证明由格式(4)得

Yk+1-θf(tk+1,Xk+1,Xk+1-m)h=Yk+(1-θ)f(tk,Xk,Xk-m)h+g(tk,Xk,Xk-m)ΔWk,

(16)

(16)式两边同时平方,移项整理得

(1-θ)2f2(tk,Xk,Xk-m)h2+g2(tk,Xk,Xk-m)(ΔWk)2+

2(1-θ)Ykf(tk,Xk,Xk-m)h+2Ykg(tk,Xk,Xk-m)ΔWk+

2(1-θ)hf(tk,Xk,Xk-m)g(tk,Xk,Xk-m)ΔWk.

因此

2(1-θ)hf(tk,Xk,Xk-m)g(tk,Xk,Xk-m)ΔWk.

(17)

注意到E(ΔWk)=0,E[(ΔWk)2]=h,而且Xk,Xk-m都是Ftk可测的,因此容易得到

(18)

又根据已知条件(9)得

(19)

根据数学期望的性质和(2)式知

(20)

将(18),(19)和(20)式代入(15)式取数学期望得

(21)

根据引理1的结论整理(21)式可得

+(1+λ2)μ2θhλ2c(k+1-m)S,

(22)

(23)

其中σ1(h;θ,λ,μ2,K1,K2,S)=(1+λ2)S(2(1-θ)2K1h+μ2+2K2).

(24)

记M=max(ρ,λ)<1,则由(24)式进一步可得

定理3 当步长h

证明由Xk=Yk+N(Xk-m)和Cauchy不等式,可得

(25)

(25)式两边取数学期望有

(26)

又根据定理2的结论,对(26)式两边同时取极限得

[1] HU Yaozhong,SALAH-ELDIN A MOHAMMED,YAN Feng.Discrete-Time Approximations of Stochastic Delay Equations:The Milstein Scheme[J].The Annals of Probability,2004,32(1A):265-314.

[2] CAO Wanrong,LIU Mingzhu,FAN Zhencheng.MS-Stability of the Euler-Maruyama Method for Stochastic Differential Delay Equations[J].Applied Mathematics and Computation,2004,159:127-135.

[3] CAO Wanrong.The Convergence and Stability of Some Numerical Methods for Stochastic Differential Delay Equation[D].Harbin:Harbin Institute of Technology,2004.

[4] CHRISTOPHER T H BAKER,EVELYN BUCKWAR.Exponential Stability inp-th Mean of Solutions,and of Convergent Euler-Type Solutions,of Stochastic Delay Differential Equations[J].Journal of Computational and Applied Mathematics,2005,184:404-427.

[5] WANG Zhiyong,ZHANG Chengjian.An Analysis of Stability of Milstein Method for Stochastic Differential Equations with Delay[J].Computers and Mathematics with Applications,2006,51:1 445-1 452.

[6] NORBERT HOFMANN,THOMAS MÜLLER-GRONBACH.A Modified Milstein Scheme for Approximation of Stochastic Delay Differential Equations with Constant Time Lag[J].Journal of Computational and Applied Mathematics,2006,197:89-121.

[7] WANG Wenqiang,HUANG Shan,LI Shoufu.Mean-Square Stability of Euler-Maruyama Methods for Nonlinear Stochastic Delay Differential Equations[J].Mathematica Numerica SINICA,2007,29(2):217-224.

[8] WANG Wenqiang,LI Shoufu,HUANG Shan.Convergence of Semi-Implicit Euler Methods for Nonlinear Stochastic Delay Differential Equations[J].Journal of Yunnan University:Natural Sciences Edition,2008,30(1):11-15.

[9] WANG Wenqiang.Convergence and Stability of Several Numerical Methods for Nonlinear Stochastic Delay Differential Equations[D].Xiangtan:Xiangtan University,2007.

[10] LUO Jiaowan.A Note on Exponential Stability inp-th Mean of Solutions of Stochastic Delay Differential Equations[J].Journal of Computational and Applied Mathematics,2007,198(1):143-148.

[11] RATHINASAMY A,BALACHANDRAN K.Mean-Square Stability of Milstein Method for Linear Hybrid Stochastic Delay Integro-Differential Equations[J].Nonlinear Analysis:Hybrid Systems,2008,2(4):1 256-1 263.

[12] ZHANG Haomin,GAN Siqing.Mean Square Convergence of One-Step Methods for Neutral Stochastic Differential Delay Equations[J].Applied Mathematics and Computation,2008,204(2):884-890.

[13] ZHANG Haomin,GAN Siqing,HU Lin.The Split-Step Backward Euler Method for Linear Stochastic Delay Differential Equations[J].Journal of Computational and Applied Mathematics,2009,225(2):558-568.

[14] WANG Wenqiang,CHEN Yanping.Mean-Square Stability of Semi-Implicit Euler Method for Nonlinear Neutral Stochastic Delay Differential Equations[J].Applied Numerical Mathematics,2011(61):696-701.

[15] MAO Xuerong.Stochastic Differential Equations and their Applications[M].Horwood:Chichester,1997.

(责任编辑 向阳洁)

Mean-SquareStabilityofθ-MethodsforNeutralNonlinearStochasticDelayDifferentialEquations

WANG Wenqiang

(School of Mathematics and Computational Science,Xiangtan University,Xiangtan 411105,Hunan China)

The mean-square stability of Euler method is investigated for nonlinear neutral stochastic delay differential equations.It is proved that the numerical method is mean-square stable(MS-stable) under a sufficient condition.

neutral stochastic delay differential equations;θ-methods;mean-square stable

1007-2985(2014)02-0010-05

2013-11-20

国家自然科学基金资助项目(11271311,11171352)

王文强(1971-),男(苗族),湖南邵阳人,湘潭大学数学与计算科学学院教授,博士后,主要从事常微分方程数值解研究.

O175.13

A

10.3969/j.issn.1007-2985.2014.02.004

猜你喜欢

均方湘潭结论
一类随机积分微分方程的均方渐近概周期解
由一个简单结论联想到的数论题
立体几何中的一个有用结论
Beidou, le système de navigation par satellite compatible et interopérable
湘潭是个好地方
湘潭红色文化软实力的提升研究
湘潭大学艺术学院作品选
湘潭80万亩超级稻增产6万吨
结论
基于抗差最小均方估计的输电线路参数辨识