Mean-square delay-distribution-dependent exponential synchronization of discrete-time Markov jump chaotic neural networks with random delay

Abstract

This paper investigates the mean square delay-distribution-dependent exponential synchronization problem of Markovian jumping discrete-time chaotic neural networks with random delays. Introduced the probability distribution of the time delay, a random variable that satisfying Bernoulli distribution is formulated to produce a new system which includes the information of the probability distribution. Based on the Lyapunov-Krasovskii functional, the Jensen's inequality theory and linear matrix inequality (LMI) technique, delay-distribution-dependent sufficient criteria are established for the discussed Markovian jumping discrete-time chaotic neural networks with random delays to be exponentially synchronized in the mean square. The derived criteria are expressed in terms of linear matrix inequalities and are dependent on the sizes as well as probabilities distribution of delays. The feasibility and the effectiveness of the presented synchronization scheme are demonstrated by one example.