Stability and synchronization for impulsive Markovian switching CVNNs: matrix measure approach

Abstract This paper devotes to the global exponential stability and synchronization problem for impulsive Markovian switching complex-valued neural networks (CVNNs) with time-varying delays. Based on the matrix measure approach and the impulsive differential inequality, some sufficient conditions are firstly derived to guarantee the impulsive network to be exponentially stable, where the exponential convergence rate is explicitly estimated. After that, the synchronization problem is investigated for the coupled impulsive complex-valued networks, and the obtained criteria are easy to be verified and implemented in practice. Finally, two examples are presented to illustrate effectiveness of the proposed theoretical results.

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