In this study, a new event-triggered impulsive control strategy is used to solve the problem of pinning synchronization in coupled impulsive dynamical neural networks with hybrid delays. In view of discontinuous coupling terms and system dynamics, the inner delay and the impulsive delay are both investigated. Compared with the traditional pinning impulsive control, event-triggered pinning impulsive control (EPIC) generates impulse instants only when an event occurs, and is therefore more in line with practical applications. In order to deal with the complexities of mixed delays, some generalized inequalities related to hybrid delays based on Lyapunov functions are proposed, which are subject to the designed event-triggered rule. Then, in order to ensure network synchronization, linear matrix inequalities (LMIs) can provide some sufficient conditions with less conservatism while a proposed event-triggered function could successfully eliminate Zeno behavior. In addition, numerical examples are presented to prove the feasibility of the presented EPIC method.

This paper investigates the problem of event-triggered impulsive synchronization control for a class of hybrid delayed dynamical complex networks. Based on the Lyapunov function method, two control strategies—distributed event-triggered impulsive control and event-triggered pinning impulsive control—are proposed to guarantee synchronization of complex networks. The first strategy does not require prior knowledge of the network topology, thereby greatly reducing implementation difficulty. The second strategy controls only a subset of nodes in the network, which significantly reduces the consumption of control resources. Several sufficient conditions are established to reveal the potential relationships among the event-triggered mechanisms, control input, and impulsive action. In addition, the proposed event-triggered mechanisms can effectively exclude Zeno behavior. Finally, some numerical examples are provided to verify the effectiveness of the theoretical results for the synchronization of delayed dynamic complex networks.

In this paper, the impulsive synchronization of a class of nonlinear multiple neural networks (MNNs) with multi-delays was considered under a dynamic event-based mechanism. To achieve a more comprehensive synchronization outcome and mitigate the conservativeness of impulsive control due to predetermined time sequences, we integrated a dynamic event-triggered strategy. This approach formed a novel control framework for generalized MNNs, where impulsive inputs were applied only under specific conditions governed by event-triggering rules. Towards the above objectives, the impulsive jumping system, resulting from dynamic component, and matrix measure method were invoked to directly increase the computational simplicity and extensibility of the study. As the outcome, the synchronization criteria for the MNNs could be achieved, and the exponential convergence rate is resolved by considering both the generalized comparison principle regarding impulsive systems and the variable parameter formula. Moreover, Zeno-freeness of the achieved triggering regulation is ensured. Finally, two numerical examples confirmed the validity of the designed approach.