Stability of switched memristive neural networks with impulse and stochastic disturbance

Abstract This paper is concerned with the problem of input-to-state stability (ISS) for a class of switched impulsive memristive neural networks with stochastic disturbance. Based on the multiple Lyapunov functions method and comparison principle, new stability results for such kind of systems are derived. The cases that all subsystems are unstable and both stable/unstable subsystems coexist are considered, respectively. Time-varying delays are taken into account in the stability analysis. The mean-square ISS delay-independent sufficient conditions are presented. Finally, numerical examples are given to illustrate the effectiveness of the proposed method.

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