New Algebraic Criteria for Global Exponential Periodicity and Stability of Memristive Neural Networks with Variable Delays

被引:1
|
作者
Zhu, Song [1 ]
Ye, Er [2 ]
Liu, Dan [1 ]
Zhou, Shengwu [1 ]
机构
[1] China Univ Min & Technol, Sch Math, Xuzhou 221116, Jiangsu, Peoples R China
[2] Southeast Univ, Sch Math, Nanjing 210096, Jiangsu, Peoples R China
关键词
Periodic solution; Exponential stability; Neural networks; Memristor; Variable delays; SYNCHRONIZATION; STABILIZATION; DESIGN;
D O I
10.1007/s11063-018-9803-y
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper concentrates on the problem of global exponential periodicity and stability of memristive neural networks with variable delays. By constructing the appropriate Lyapunov functionals and utilizing some inequality techniques, new algebraic criteria are proposed to guarantee the existence and global exponential stability of periodic solution of the considered system. In addition, the proposed theoretical results not only expand and complement the earlier publications, but also are easy to be checked with the parameters of system itself. A numerical example is given to demonstrate the effectiveness of our results.
引用
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页码:1749 / 1766
页数:18
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