New results on almost periodic solutions for CNNs with time-varying leakage delays

被引：29
|
作者：
Xu, Yanli [1 ]
机构：
[1] Xiangnan Coll, Dept Math, Chenzhou 423000, Hunan, Peoples R China
来源：
NEURAL COMPUTING & APPLICATIONS | 2014年 / 25卷 / 06期
关键词：
Cellular neural networks; Almost periodic solution; Exponential stability; Time-varying delay; Leakage term; CELLULAR NEURAL-NETWORKS; EXPONENTIAL STABILITY;
D O I：
10.1007/s00521-014-1610-4
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, based on the exponential dichotomy theory and contraction mapping fixed point theorem, we obtain some sufficient conditions ensuring the global exponential stability of almost periodic solutions for a new generalized cellular neural network model with time-varying delays in leakage (or forgetting) terms. Our results complement some recent ones. Moreover, an illustrative example and its numerical simulation are given to demonstrate the effectiveness of the obtained results.
引用
收藏
页码：1293 / 1302
页数：10
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