Event-triggered network-based synchronization of delayed neural networks

This paper is concerned with the problem of event-triggered network-based synchronization for a class of delayed neural networks. By introducing an event generator in the control loop, the model of event-triggered master–slave synchronization frame is constructed. Considering the effect of the communication network including transmission delay and stochastic fluctuation, an event-triggered error system of master system and slave system is formulated. By using the Lyapunov functional method, some delay-dependent synchronization criteria in terms of linear matrix inequality are proposed to ensure the mean square synchronization between the master system and the slave system. A singular value decomposition lemma is introduced to solve the control design problem for the case of the lower bound of neuron activation function is nonzero, which is different from the previous literature. Two illustrative examples are provided to demonstrate the limited network bandwidth could be saved by using the proposed design scheme.