Convergence of Monte Carlo simulations involving the mean-reverting square root process [PDF]
, 2005 The mean-reverting square root process is a stochastic differential equation (SDE) that has found considerable use as a model for volatility, interest rate, and other financial quantities.
Mao, X., Higham, D.J.
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Asymptotical Mean Square Stability of Cohen-Grossberg Neural Networks with Random Delay
Journal of Inequalities and Applications, 2010 The asymptotical mean-square stability analysis problem is considered for a class of Cohen-Grossberg neural networks (CGNNs) with random delay. The evolution of the delay is modeled by a continuous-time homogeneous Markov process with a finite number of
Zhang Hanjun, Zou Jiezhong, Zhu Enwen
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Mean Square Exponential Stability of a Class of Stochastic Rcellular Neural Networks
Journal of Harbin University of Science and Technology, 2020 In this paper, the problem of the mean square exponential stability of a class of impulsive stochastic reactiondiffusion cellular neural networks (CNNs) with transmission delay and distributed delay, and parameter uncertainties is discussed.
LIU Xin, CHEN Lili, HUANG Shuai
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Mean-square exponential input-to-state stability of stochastic inertial neural networks
Advances in Difference Equations, 2021 By introducing some parameters perturbed by white noises, we propose a class of stochastic inertial neural networks in random environments. Constructing two Lyapunov–Krasovskii functionals, we establish the mean-square exponential input-to-state ...
Wentao Wang, Wei Chen
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Almost sure exponential stability of backward Euler–Maruyama discretizations for hybrid stochastic differential equations [PDF]
, 2011 This is a continuation of the first author's earlier paper [1] jointly with Pang and Deng, in which the authors established some sufficient conditions under which the Euler-Maruyama (EM) method can reproduce the almost sure exponential stability of the ...
Shen, Yi, Mao, Xuerong, Gray, Alison
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Mean-square stability and convergence of compensated split-step θ-method for nonlinear jump diffusion systems [PDF]
Mathematics and Modeling in Finance, 2021 In this paper, the existence and uniqueness of the numerical solution of the Stochastic Differential Equations with Jumps(SDEwJs) under the one side Lipschitz conditions and polynomial growth conditions are presented.
Ali Soheili +2 more
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Mean square exponential stability of stochastic function differential equations in the G-framework
Open Mathematics, 2023 This research focuses on the stochastic functional differential equations driven by G-Brownian motion (G-SFDEs) with infinite delay. It is proved that the trivial solution of a G-SFDE with infinite delay is exponentially stable in mean square. An example
Li Guangjie, Hu Zhipei
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Mean-Square Stability of Uncertain Delayed Stochastic Systems Driven by G-Brownian Motion
Mathematics, 2023 This paper investigates the mean-square stability of uncertain time-delay stochastic systems driven by G-Brownian motion, which are commonly referred to as G-SDDEs.
Zhengqi Ma +3 more
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A Mean Square Stability Test for Markovian Jump Linear Systems
Trends in Computational and Applied Mathematics, 2008 This paper proposes a test for the mean square stability problem for discrete-time linear systems subject to random jumps in the parameters, described by an underlying finite-state Markov chain.
C. Nespoli, J.B.R. do Val
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Mean square exponential stability of stochastic delay cellular neural networks
Electronic Journal of Qualitative Theory of Differential Equations, 2013 By constructing suitable Lyapunov functionals and combining with matrix inequality technique, a new simple sufficient condition is presented for the exponential stability of stochastic cellular neural networks with discrete delays. The condition contains
Yingxin Guo
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