Stability of Markovian jumping recurrent neural networks with discrete and distributed time-varying delays

Abstract In this paper, global stability of Markovian jumping recurrent neural networks with discrete and distributed delays (MJRNN) is considered. A novel linear matrix inequality (LMI) based stability criterion is obtained by using Lyapunov functional theory to guarantee the asymptotic stability of Markovian jumping recurrent neural networks with discrete and distributed delays. By applying Lyapunov method and some inequality techniques, several sufficient conditions are obtained under which the delayed neural networks are stable. Finally, numerical examples are given to demonstrate the correctness of the theoretical results.

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