TY - JOUR
T1 - Event-Triggered Finite-Time Synchronization Control for Quaternion-Valued Memristive Neural Networks by an Non-Decomposition Method
AU - Ping, Jing
AU - Zhu, Song
AU - Shi, Mingxiao
AU - Wu, Siman
AU - Shen, Mouquan
AU - Liu, Xiaoyang
AU - Wen, Shiping
N1 - Publisher Copyright:
© 2013 IEEE.
PY - 2023/11/1
Y1 - 2023/11/1
N2 - Applying the event-triggered control, this article 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.
AB - Applying the event-triggered control, this article 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.
KW - Finite-time synchronization
KW - Zeno behavior
KW - event-triggered control
KW - quaternion-valued memristive neural networks (QVMNNs)
UR - http://www.scopus.com/inward/record.url?scp=85153483303&partnerID=8YFLogxK
U2 - 10.1109/TNSE.2023.3268101
DO - 10.1109/TNSE.2023.3268101
M3 - 文章
AN - SCOPUS:85153483303
SN - 2327-4697
VL - 10
SP - 3609
EP - 3619
JO - IEEE Transactions on Network Science and Engineering
JF - IEEE Transactions on Network Science and Engineering
IS - 6
ER -