Almost periodic solution to Cohen-Grossberg-type BAM networks with distributed delays

被引:19
作者
Xiang, Hongjun [1 ]
Wang, Jinhua [1 ]
Cao, Jinde [2 ]
机构
[1] Xiangnan Univ, Dept Math, Chenzhou 423000, Peoples R China
[2] Southeast Univ, Dept Math, Nanjing 210096, Peoples R China
关键词
Cohen-Grossberg-type; BAM neural networks; Almost periodic solution; Exponential stability; GLOBAL EXPONENTIAL STABILITY; ASSOCIATIVE MEMORY NETWORKS; NEURAL-NETWORKS; CONTINUOUS-TIME;
D O I
10.1016/j.neucom.2009.05.014
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, a class of Cohen-Grossberg-type bi-directional associative memory (BAM) neural networks with distributed delays is discussed. Based on inequality analysis method and combining the exponential dichotomy with fixed point theorem, some novel sufficient conditions are obtained to ensure the existence and globally exponential stability of almost periodic solution to this system. Moreover, an example is given to demonstrate the feasibility of our results. (C) 2009 Elsevier B.V. All rights reserved.
引用
收藏
页码:3751 / 3759
页数:9
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