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Existence and exponentially stability of anti-periodic solutions of two-neural networks with infinite delays

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成果类型:
期刊论文
作者:
Xu, Changjin*;Liao, Maoxin
通讯作者:
Xu, Changjin
作者机构:
[Xu, Changjin] Guizhou Key Laboratory of Economics System Simulation, Guizhou University of Finance and Economics, Guiyang, 550004, China
[Liao, Maoxin] School of Mathematics and Physics, University of South China, Hengyang, 421001, China
通讯机构:
Guizhou Key Laboratory of Economics System Simulation, Guizhou University of Finance and Economics, Guiyang, China
语种:
英文
关键词:
Anti-Periodic Solution;Delay;Exponential Stability;Neural Networks
期刊:
Journal of Computational and Theoretical Nanoscience
ISSN:
1546-1955
年:
2015
卷:
12
期:
11
页码:
4383-4391
机构署名:
本校为其他机构
院系归属:
数理学院
摘要:
This paper is concerned with the existence and exponential stability of anti-periodic solutions of two-neural networks with variable and unbounded delays. Using some analysis skills and Lyapunov method, a series of sufficient conditions for the existence and exponential stability of anti-periodic solutions to two-neural networks with variable and unbounded delays are presented. Our results are...

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