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Novel Exponential Synchronization criterion of Markov jump Neural Networks with Additive Time-varying Delays *

This paper addresses the Exponential Synchronization Problem (ESP) for a class of Markov Jump Neural Networks (MJNNs) with Additive Time-varying Delays (ATVDs). Firstly, a new Free-matrix Exponential-type Inequality (FMEI), which can derive a tighter bound of Exponential-type Integral Quadratic Terms (EIQTs), is proposed. Secondly, to capture more information about the attenuation exponent, ATVDs and Markov jump parameters, a novel Lyapunov-Krasovskii functional is constructed. Then, by using the new FMEI and other analytical techniques, a less conservative criterion guaranteeing the stochastic synchronization of master-slave system is described in form of Linear Matrix Inequalities (LMIs). Finally, a numerical example is given to illustrate the effectiveness of the derived result.