This paper is concerned with the global asymptotic stability of a class of stochastic bidirectional associative memory neural networks with both multiple discrete and distributed time-varying delays. A new criterion of asymptotic stability is derived in terms of linear matrix inequality, which can be efficiently solved by a standard numerical software. An illustrative numerical example is also given to show the applicability and effectiveness of the proposed results. [ABSTRACT FROM AUTHOR]
The aim of this paper is to construct a non-standard finite difference (NSFD) scheme that can be used to calculate numerical solutions for an epidemic model with vaccination. Here, the NSFD method is employed to derive a set of difference equations for the epidemic model with vaccination. We show that when, the discretized model preserves positivity and global dynamics of the continuous model. Numerical simulation illustrates the effectiveness of our results. [ABSTRACT FROM PUBLISHER]