Finite-Time Synchronization for Complex-Valued Recurrent Neural Networks with Time Delays

被引：11
|
作者：
Zhang, Ziye [1 ,2 ]
Liu, Xiaoping [3 ]
Lin, Chong [2 ]
Chen, Bing [2 ]
机构：
[1] Shandong Univ Sci & Technol, Coll Math & Syst Sci, Qingdao 266590, Peoples R China
[2] Qingdao Univ, Inst Complex Sci, Qingdao 266071, Peoples R China
[3] Lakehead Univ, Dept Elect Engn, Thunder Bay, ON P7B 5E1, Canada
来源：
COMPLEXITY | 2018年
基金：
加拿大自然科学与工程研究理事会; 中国国家自然科学基金;
关键词：
GLOBAL EXPONENTIAL STABILITY; VARIABLE CHAOTIC SYSTEMS; UNKNOWN-PARAMETERS; DYNAMICAL NETWORKS; NONLINEAR-SYSTEMS; HOPF-BIFURCATION; NEUTRAL-TYPE; STABILIZATION; DISSIPATIVITY; DISCRETE;
D O I：
10.1155/2018/8456737
中图分类号：
O1 [数学];
学科分类号：
0701 ; 070101 ;
摘要：
This paper focuses on the finite-time synchronization analysis for complex-valued recurrent neural networks with time delays. First, two kinds of common activation functions appearing in the existing references are combined together and more general assumptions are given. To achieve our aim, a nonlinear delayed controller with two independent parameters different from the existing ones is provided, which leads to great difficulty. To overcome it, a newly developed inequality is used. Then, via Lyapunov function approach, some criteria are derived to guarantee the finite-time synchronization of the considered system, and the settling time for synchronization is also estimated. Finally, two numerical simulations are given to support the effectiveness and advantages of the obtained results.
引用
收藏
页数：14
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