Existence and global exponential stability of periodic solution to self-connection BAM neural networks with delays

被引:35
|
作者
Liu, ZG
Chen, AP [1 ]
Huang, LH
机构
[1] Xiangtan Univ, Dept Math, Chenzhou 423000, Peoples R China
[2] Hunan Univ, Coll Math & Econometr, Changsha 410082, Peoples R China
基金
中国国家自然科学基金;
关键词
BAM neural networks; exponential stability; periodic solution; delays;
D O I
10.1016/j.physleta.2004.05.055
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
By using the continuation theorem of Mawhin's coincidence degree theory, Lyapunov functional method and some analytical techniques, some sufficient conditions are obtained ensuring existence and global exponential stability of periodic solution of the self-connection BAM neural networks with periodic coefficients and delays. These results are more effective than the ones in [IEEE Trans. Circuits Systems 50 (2003) 1162] for some neural networks, which has an important leading significance in the designing globally exponentially stable and periodic oscillatory BAM neural networks with self-connection. (C) 2004 Elsevier B.V. All rights reserved.
引用
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页码:127 / 143
页数:17
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