Event-Triggered Finite-Time Synchronization Control for Quaternion-Valued Memristive Neural Networks by an Non-Decomposition Method
Jing Ping, Song Zhu, Mingxiao Shi, Siman Wu, Mouquan Shen, Xiaoyang Liu, Shiping Wen
Abstract
Applying the event-triggered control, this paper discusses the finite-time synchronization issue of quaternion-valued memristive neural networks (QVMNNs) with time-varying delays. By employing the improved one norm and sign function of quaternion, the QVMNNs can be analyzed as an entirety without any decomposition. To relieve the communication pressure, a proper event-triggered controller is designed, then the event-triggered conditions and some criteria are also established to guarantee finite-time synchronization. Moreover, the synchronization time is estimated by direct analysis, and the positive lower bound of the inter-event time is obtained to get rid of the Zeno behavior. In addition, according to the acquired event-triggered scheme, a self-triggered scheme is further provided to refrain from continuous detection. Ultimately, the validity of the obtained theoretical results is demonstrated by a numerical simulation.