Impulsive exponential synchronization of randomly coupled neural networks with Markovian jumping and mixed model-dependent time delays.

Abstract

In this paper, the exponential synchronization problem for an array of N randomly coupled neural networks with Markovian jump and mixed model-dependent time delays via impulsive control is investigated. The jump parameters are determined by a continuous-time, discrete-state Markovian chain, and the mixed time delays under consideration comprise both discrete and continuous distributed delays. By making use of the Kronecker product and some useful techniques, a novel Lyapunov-Krasovskii functional suitable for handling distributed delays was proposed and then we show that the addressed synchronization problem is solvable if a set of linear matrix inequalities (LMIs) are feasible. The results presented in this paper generalize and improve many known results. Two numerical examples are also given to show the effectiveness of the theoretical results.