Periodic oscillation for discrete-time Hopfield neural networks

被引：34
作者：
Guo, SJ [1 ]
Huang, LH [1 ]
机构：
[1] Hunan Univ, Coll Math & Econometr, Changsha 410082, Hunan, Peoples R China
来源：
PHYSICS LETTERS A | 2004年 / 329卷 / 03期
基金：
中国国家自然科学基金;
关键词：
periodic solution; delay difference system; Hopfield neural network; coincidence theory;
D O I：
10.1016/j.physleta.2004.07.007
中图分类号：
O4 [物理学];
学科分类号：
0702 ;
摘要：
By using the continuation theorem of coincidence degree theory, we obtain some sufficient conditions for the existence of periodic solutions of discrete-time Hopfield neural network model. Our results can be applied to neural networks with a broad range of activation functions assuming neither differentiability nor strict monotonicity. Moreover, these conclusions are presented in terms of system parameters and can be easily verified. (C) 2004 Elsevier B.V. All rights reserved.
引用
收藏
页码：199 / 206
页数：8
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