Stability and Synchronization Analysis of Discrete-Time Delayed Neural Networks with Discontinuous Activations

被引：4
|
作者：
Wang, Jinling [1 ]
Jiang, Haijun [1 ]
Ma, Tianlong [2 ]
Hu, Cheng [1 ]
机构：
[1] Xinjiang Univ, Coll Math & Syst Sci, Urumqi 830046, Xinjiang, Peoples R China
[2] Qinghai Univ, Xining 810016, Qinghai, Peoples R China
来源：
NEURAL PROCESSING LETTERS | 2019年 / 50卷 / 02期
关键词：
Discrete-time neural networks; Discontinuous activations; Synchronization; Stability; GLOBAL ASYMPTOTIC STABILITY; EXPONENTIAL STABILITY; CONVERGENCE; BEHAVIOR;
D O I：
10.1007/s11063-018-9943-0
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, both stability and synchronization of discrete-time delayed neural networks with discontinuous activations are investigated. By means of functional differential inclusions and Kakutani's fixed point theorem, conditions are derived to ensure the existence and uniqueness of the solution. Besides, we obtain some novel sufficient conditions for global attractivity and asymptotic stability of the discontinuous discrete-time neural networks via the Halanay-type inequality and the comparison principle. Furthermore, under weaker conditions than Lipschitz conditions, we also select two different controllers to guarantee synchronization of the discrete-time neural networks with discontinuous activations. Finally, some examples with numerical simulation are given to demonstrate the effectiveness of the obtained results.
引用
收藏
页码：1549 / 1570
页数：22
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