Robust stability of impulsive switched neural networks with multiple time delays
Abstract A class of switched neural networks (SNNs) in the presence of parameter uncertainties, impulsive effects, and both variable and continuously distributed delays are investigated. Firstly, the existence and uniqueness conditions of equilibrium point of each subsystem are proposed, which implies that the addressed SNNs has a unique equilibrium point. Secondly, we derive several sufficient conditions for robust exponential stability under average dwell time (ADT) switching and arbitrary switching, respectively. These conditions are formulated in terms of algebraic inequalities and M-matrices and are derived by employing inequality technique incorporated with the idea of vector Lyapunov function. Lastly, the less conservativeness and effectiveness of the obtained results over some existing literature are verified by simulation examples.