Strong discrete time approximation of stochastic differential equations with time delay
Mathematics and Computers in Simulation
Strong Convergence of Euler-Type Methods for Nonlinear Stochastic Differential Equations
SIAM Journal on Numerical Analysis
Journal of Computational and Applied Mathematics
Exponential Stability of Uncertain Stochastic Neural Networks with Markovian Switching
Neural Processing Letters
Stability of stochastic θ-methods for stochastic delay integro-differential equations
International Journal of Computer Mathematics
Non-fragile observer-based H ∞ control for neutral stochastic hybrid systems with time-varying delay
Neural Computing and Applications - Special Issue: ISNN 2010
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This paper is concerned with the general mean-square (GMS) stability and mean-square (MS) stability of stochastic $$\theta $$-methods for stochastic delay Hopfield neural networks under regime switching. The sufficient conditions to guarantee GMS-stability and MS-stability of stochastic $$\theta $$-methods are given. Finally, an example is used to illustrate the effectiveness of our result.