数学
分段
微分包含
外稃(植物学)
独特性
人工神经网络
四元数
常量(计算机编程)
理论(学习稳定性)
平衡点
应用数学
微分方程
数学分析
计算机科学
几何学
生物
机器学习
程序设计语言
禾本科
生态学
作者
Jingjing Wang,Song Zhu,Xiaoyang Liu,Shiping Wen
标识
DOI:10.1016/j.neunet.2023.02.030
摘要
This paper studies the global Mittag-Leffler (M-L) stability problem for fractional-order quaternion-valued memristive neural networks (FQVMNNs) with generalized piecewise constant argument (GPCA). First, a novel lemma is established, which is used to investigate the dynamic behaviors of quaternion-valued memristive neural networks (QVMNNs). Second, by using the theories of differential inclusion, set-valued mapping, and Banach fixed point, several sufficient criteria are derived to ensure the existence and uniqueness (EU) of the solution and equilibrium point for the associated systems. Then, by constructing Lyapunov functions and employing some inequality techniques, a set of criteria are proposed to ensure the global M-L stability of the considered systems. The obtained results in this paper not only extends previous works, but also provides new algebraic criteria with a larger feasible range. Finally, two numerical examples are introduced to illustrate the effectiveness of the obtained results.
科研通智能强力驱动
Strongly Powered by AbleSci AI