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四元数 valued 忆阻器神经网络的混合时滞固定时间同步。

Fixed-time synchronization for quaternion-valued memristor-based neural networks with mixed delays.

机构信息

Department of Mathematics, Faculty of Science and Technology, University of Macau, Macau, 999078, China.

College of Mathematics and Computer Science, Zhejiang Normal University, Jinhua, 321004, China.

出版信息

Neural Netw. 2023 Aug;165:274-289. doi: 10.1016/j.neunet.2023.05.045. Epub 2023 Jun 1.

Abstract

In this paper, the fixed-time synchronization (FXTSYN) of unilateral coefficients quaternion-valued memristor-based neural networks (UCQVMNNs) with mixed delays is investigated. A direct analytical approach is suggested to obtain FXTSYN of UCQVMNNs utilizing one-norm smoothness in place of decomposition. When dealing with drive-response system discontinuity issues, use the set-valued map and the differential inclusion theorem. To accomplish the control objective, innovative nonlinear controllers and the Lyapunov functions are designed. Furthermore, some criteria of FXTSYN for UCQVMNNs are given using inequality techniques and the novel FXTSYN theory. And the accurate settling time is obtained explicitly. Finally, in order to show that the obtained theoretical results are accurate, useful, and applicable, numerical simulations are presented at the conclusion.

摘要

本文研究了具有混合时滞的单边系数四元数 valued 忆阻器神经网络(UCQVMNNs)的固定时间同步(FXTSYN)。提出了一种直接解析方法,利用范数平滑代替分解来获得 UCQVMNN 的 FXTSYN。在处理驱动-响应系统不连续性问题时,使用集值映射和微分包含定理。为了实现控制目标,设计了新颖的非线性控制器和李雅普诺夫函数。此外,还利用不等式技术和新的 FXTSYN 理论给出了 UCQVMNNs 的 FXTSYN 准则。并明确得到了精确的稳定时间。最后,为了说明所得到的理论结果是准确的、有用的和适用的,在结论中给出了数值模拟。

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