Strong Convergence Order of the Projected Euler-Maruyama Method for Neutral Stochastic Delay Differential Equations Under a Global Monotone Condition

Chao Yue

Communications on Applied Mathematics and Computation ›› : 1 -23.

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Communications on Applied Mathematics and Computation ›› :1 -23. DOI: 10.1007/s42967-025-00534-x
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Strong Convergence Order of the Projected Euler-Maruyama Method for Neutral Stochastic Delay Differential Equations Under a Global Monotone Condition

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Abstract

This paper is concerned with the strong convergence of the projected Euler-Maruyama (PEM) method for neutral stochastic delay differential equations (NSDDEs) with variable delays. First, the notions of C-stability and B-consistency are defined for NSDDEs. Subsequently, under a global monotone condition, a fundamental theorem on strong convergence is established for general one-step methods applied to nonlinear NSDDEs. We then construct the PEM method, an explicit one-step scheme, and prove its C-stability, B-consistency, and strong convergence of order 1/2. Finally, a numerical experiment is presented to validate the results.

Keywords

Neutral stochastic delay differential equations (NSDDEs) / Strong convergence / Projected Euler-Maruyama (PEM) method / C-stability / B-consistency / Non-global Lipschitz condition / 65C20 / 65L20 / 60H35

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Chao Yue. Strong Convergence Order of the Projected Euler-Maruyama Method for Neutral Stochastic Delay Differential Equations Under a Global Monotone Condition. Communications on Applied Mathematics and Computation 1-23 DOI:10.1007/s42967-025-00534-x

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References

[1]

Bao, H., Cao, J.: Stochastic global exponential stability for neutral-type impulsive neural networks with mixed time-delays and Markovian jumping parameters. Commun. Nonlinear Sci. Numer. Simul. 16(9), 3786–3791 (2011)

[2]

Beyn W-J, Isaak E, Kruse R. Stochastic C-stability and B-consistency of explicit and implicit Euler-type schemes. J. Sci. Comput., 2016, 67(3): 955-987.

[3]

Beyn W-J, Isaak E, Kruse R. Stochastic C-stability and B-consistency of explicit and implicit Milstein-type schemes. J. Sci. Comput., 2017, 70(3): 1042-1077.

[4]

Dekker, K.: Stability of Runge-Kutta Methods for Stiff Nonlinear Differential Equations. CWI Monographs, vol. 2. North-Holland, Amsterdam (1984)

[5]

Deng S, Fei C, Fei W, Mao X. Tamed EM schemes for neutral stochastic differential delay equations with superlinear diffusion coefficients. J. Comput. Appl. Math., 2021, 388113269

[6]

Gan S, Henri S, Zhang H. Mean square convergence of stochastic θ\documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$$\theta $$\end{document}-methods for nonlinear neutral stochastic differential delay equations. Int. J. Numer. Anal. Model., 2011, 8(2): 201-213. DOI:

[7]

Guo C, O’Regan D, Deng F, Agarwal RP. Fixed points and exponential stability for a stochastic neutral cellular neural network. Appl. Math. Lett., 2013, 26(8): 849-853.

[8]

Hairer, E., Wanner, G.: Solving Ordinary Differential Equations. II: Stiff and Differential-Algebraic Problems, Volume 14 of Springer Series in Computational Mathematics, 2nd edn. Springer, Berlin (1996)

[9]

Higham DJ. An algorithmic introduction to numerical simulation of stochastic differential equations. SIAM Rev., 2001, 43(3): 525-546.

[10]

Janković B, Stopić S, Güven A, Friedrich B. Kinetic modeling of thermal decomposition of zinc ferrite from neutral leach residues based on stochastic geometric model. J. Magn. Magn. Mater., 2014, 358: 105-118.

[11]

Ji Y, Yuan C. Tamed EM scheme of neutral stochastic differential delay equations. J. Comput. Appl. Math., 2017, 326: 337-357.

[12]

Kolmanovskii V, Koroleva N, Maizenberg T, Mao X, Matasov A. Neutral stochastic differential delay equations with Markovian switching. Stoch. Anal. Appl., 2003, 21(4): 819-847.

[13]

Kolmanovskii V, Nosov V. Stability and Periodic Modes of Control Systems with Aftereffect, 1981, Moscow. Nauka

[14]

Lan G, Wang Q. Strong convergence rates of modified truncated EM methods for neutral stochastic differential delay equations. J. Comput. Appl. Math., 2019, 362: 83-98.

[15]

Li M, Huang C. Projected Euler-Maruyama method for stochastic delay differential equations under a global monotonicity condition. Appl. Math. Comput., 2020, 366124733

[16]

Li M, Huang C, Chen Z. Compensated projected Euler-Maruyama method for stochastic differential equations with superlinear jumps. Appl. Math. Comput., 2021, 393125760

[17]

Mao X, Sabanis S. Numerical solutions of stochastic differential delay equations under local Lipschitz condition. J. Comput. Appl. Math., 2003, 151(1): 215-227.

[18]

Milošević M. Highly nonlinear neutral stochastic differential equations with time-dependent delay and the Euler-Maruyama method. Math. Comput. Model., 2011, 54(9): 2235-2251.

[19]

Milošević M. Convergence and almost sure exponential stability of implicit numerical methods for a class of highly nonlinear neutral stochastic differential equations with constant delay. J. Comput. Appl. Math., 2015, 280: 248-264.

[20]

Milošević M. Convergence and almost sure polynomial stability of the backward and forward-backward Euler methods for highly nonlinear pantograph stochastic differential equations. Math. Comput. Simul., 2018, 150: 25-48.

[21]

Petrović A, Milošević M. The truncated Euler-Maruyama method for highly nonlinear neutral stochastic differential equations with time-dependent delay. Filomat, 2021, 35(7): 2457-2484.

[22]

Strehmel K, Weiner R, Podhaisky H. Numerik gewöhnlicher Differentialgleichungen: nichtsteife, steife und differential-algebraische Gleichungen, 20122Wiesbaden. Springer Spektrum.

[23]

Tan L, Yuan C. Strong convergence of a tamed theta scheme for NSDDEs with one-sided Lipschitz drift. Appl. Math. Comput., 2018, 338: 607-623. DOI:

[24]

Wu F, Mao X. Numerical solutions of neutral stochastic functional differential equations. SIAM J. Numer. Anal., 2008, 46(4): 1821-1841.

[25]

Yan Z, Xiao A, Tang X. Strong convergence of the split-step theta method for neutral stochastic delay differential equations. Appl. Numer. Math., 2017, 120: 215-232.

[26]

Yue C. Strong convergence of compensated split-step theta methods for SDEs with jumps under monotone condition. Appl. Math. Comput., 2019, 340: 72-83. DOI:

[27]

Yue C, Zhao L. Strong convergence of the split-step backward Euler method for stochastic delay differential equations with a nonlinear diffusion coefficient. J. Comput. Appl. Math., 2021, 382113087

[28]

Zhang H, Gan S. Mean square convergence of one-step methods for neutral stochastic differential delay equations. Appl. Math. Comput., 2008, 204(2): 884-890. DOI:

[29]

Zhou S, Fang Z. Numerical approximation of nonlinear neutral stochastic functional differential equations. J. Appl. Math. Comput., 2013, 41(1/2): 427-445.

[30]

Zhou S, Jin H. Strong convergence of implicit numerical methods for nonlinear stochastic functional differential equations. J. Comput. Appl. Math., 2017, 324(1): 241-257.

[31]

Zhou S, Wu F. Convergence of numerical solutions to neutral stochastic delay differential equations with Markovian switching. J. Comput. Appl. Math., 2009, 229(1): 85-96.

Funding

the Key Research Program of Higher Education Institutions of Henan Province(24B110019)

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Shanghai University

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