On stability analysis of random impulsive and switching neural networks

Abstract The problem of stability analysis for a general class of random impulsive and switching neural networks is studied in this paper, in which both the continuous dynamics and the impulsive jumps are subject to random disturbances. First, a result concerning with the existence and uniqueness of solutions to random impulsive and switching neural networks is developed under some general conditions. Then, by means of time-varying discretized Lyapunov function approach and dwell time technique, some criteria guaranteeing global asymptotic stability and noise-to-state stability are established, in which the impulse and switching effects are characterized in an aggregated form. Two numerical examples are employed to explain and illuminate the efficiency of the developed results.

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