Passivity-based state synchronization for semi-Markov jump coupled chaotic neural networks with randomly occurring time delays

In this work, the problem of passivity-based synchronization for coupled chaotic neural networks with randomly occurring time delays is addressed. The topology switching of the networks is subject to the semi-Markov process. Some Bernoulli random variables are used to simulate the randomly occurring phenomena of the aforesaid networks. Furthermore, the main objective is to develop the synchronization criteria such that the considered networks can achieve global stochastic synchronization and conform to the passive performance index. Subsequently, by using some relatively advantageous inequalities and reasonable matrix transformation techniques, some available synchronization criteria are derived. Ultimately, an example is presented to illustrate the applicability and availability of the method proposed.