Event-Triggered Finite-Time Synchronization Control for Quaternion-Valued Memristive Neural Networks by an Non-Decomposition Method

被引:8
|
作者
Ping, Jing [1 ]
Zhu, Song [1 ]
Shi, Mingxiao [1 ]
Wu, Siman [1 ]
Shen, Mouquan [2 ]
Liu, Xiaoyang [3 ]
Wen, Shiping [4 ]
机构
[1] China Univ Min & Technol, Sch Math, Xuzhou 221116, Peoples R China
[2] Nanjing Technol Univ, Coll Elect Engn & Control Sci, Nanjing 211816, Peoples R China
[3] Jiangsu Normal Univ, Sch Comp Sci & Technol, Xuzhou 221116, Peoples R China
[4] Univ Technol Sydney, Ctr Artificial Intelligence, Sydney, NSW 2007, Australia
基金
中国国家自然科学基金;
关键词
Synchronization; Quaternions; Artificial neural networks; Memristors; Delay effects; Behavioral sciences; Neurons; Finite difference methods; Neural networks; Event detection; Finite-time synchronization; quaternion-valued memristive neural networks (QVMNNs); event-triggered control; Zeno behavior; MITTAG-LEFFLER STABILITY; PARAMETERS;
D O I
10.1109/TNSE.2023.3268101
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
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.
引用
收藏
页码:3609 / 3619
页数:11
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