Drive-response synchronization of uncertain Markov jump generalized neural networks with interval time varying delays via decentralized event-triggered communication scheme. Issue 11 (July 2020) - Vadivel, R.; Ali, M. Syed; Joo, Young Hoon
Abstract: This paper investigates the synchronization problem of uncertain Markov jump generalized neural networks with interval time varying delays using decentralized event-triggered approach. We present a decentralized event-triggered scheme is utilized to decide if the sensor estimations ought to be sent out or not. Every sensor can choose the transmitted sensor estimations locally as indicated by the related event-triggered condition. By constructing an appropriate Lyapunov–Krasovskii functional (LKF) both continuous and discontinuous LKF, handled by the Jensen's inequality, peng-park's inequality (PPI) and a new Wirtinger-based integral inequality (WII) technique respectively. A simple and less conservative synchronization criterion is given to ensure the master systems synchronize with the slave systems by using the linear matrix inequality (LMI) approach. The Lyapunov method is employed to derive a sufficient condition such that the error system is stochastically stable. Moreover, the desired controller gains and event-triggered parameters are derived provided that the sufficient condition is satisfied. Finally, numerical examples are included to show that the results obtained from the proposed method provide less conservative results, which support the superiority of our criteria.