Event-triggered finite-time quantized synchronization of uncertain delayed neural networks

A novel finite-time synchronization design is developed for uncertain delayed neural networks with event-triggered mechanisms and input quantizations. Initially, an error model is established which characterizes the effects of the event triggering scheme and quantization within a unified framework. Under such a synchronization model, some matrix inequality-based sufficient conditions for the existence of the finite-time synchronization is deduced by using Lyapunov functional approach and free-weighting matrix techniques. Additionally, utilizing variable separation approach, a co-design algorithm for the suitable finite-time synchronization controller and event-triggered matrix parameter are derived in terms of the feasibility of linear matrix inequalities. Besides, an example is illustrated to verify the effectiveness of the proposed method.