Dynamic Event-Triggered Stabilization for Markov Jump Delayed Complex-Valued Neural Networks
Yuan Wang, Huaicheng Yan, Min Xue, Meng Wang, Jing Zhou · 2021 China Automation Congress (CAC) · 2021
The paper addresses the problem of stabilization for Markov jump complex-valued neural networks with time-varying delays. The Markov model is adopted to describe the abrupt changes in the parameters of system. In order to make better use of the limited network bandwidth, a novel dynamic event-triggered scheme (DETS) is developed to schedule the data transmission. Based on the Lyapunov stability theory, the delay-dependent stability criterion is presented. Finally, the simulation results are given to verify the usefulness of the proposed stabilizing method.