Stability analysis of stochastic neural networks with Markovian jump parameters using delay-partitioning approach

摘要

In this paper, the problem of mean square asymptotic stability of stochastic neural networks with Markovian jumping parameters is considered. By choosing an augmented Lyapunov-Krasovskii functional and utilizing the delay-partitioning method, novel delay-dependent mean square asymptotic stability conditions are derived in terms of linear matrix inequalities. Numerical examples are given to illustrate the effectiveness of the proposed approach.