Event-Based Impulsive Control for Heterogeneous Neural Networks with Communication Delays

The quasi-synchronization for a class of general heterogeneous neural networks is explored by event-based impulsive control strategy. Compared with the traditional average interval (AII) method, instead, an event-triggered mechanism (ETM) employed to determine instants, in which case subjectivity selecting controlling sequence can be eliminated. In addition, considering fact that communication delay inevitable between allocation and execution instructions practice, we further nominate ETM centered on delays aperiodic sampling, more accessible affordable, yet straightforwardly avoid Zeno behavior. Hence, basis novel strategy, network model investigated some conditions are also achieved. Finally, two numerical simulations afforded validate efficacy theoretical results.