Global asymptotic stability analysis of bidirectional associative memory neural networks with distributed delays and impulse

被引:33
|
作者
Huang, Zai-Tang
Luo, Xiao-Shu [1 ]
Yang, Qi-Gui
机构
[1] Guangxi Normal Univ, Dept Phys & Elect Sci, Guilin 541004, Peoples R China
[2] Guangxi Normal Univ, Dept Math, Guilin 541004, Peoples R China
[3] S China Univ Technol, Sch Math Sci, Guangzhou 510640, Guangdong, Peoples R China
基金
中国国家自然科学基金;
关键词
D O I
10.1016/j.chaos.2006.03.112
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
Many systems existing in physics, chemistry, biology, engineering and information science can be characterized by impulsive dynamics caused by abrupt jumps at certain instants during the process. These complex dynamical behaviors can be model by impulsive differential system or impulsive neural networks. This paper formulates and studies a new model of impulsive bidirectional associative memory (BAM) networks with finite distributed delays. Several fundamental issues, such as global asymptotic stability and existence and uniqueness of such BAM neural networks with impulse and distributed delays, are established. (C) 2006 Published by Elsevier Ltd.
引用
收藏
页码:878 / 885
页数:8
相关论文
共 50 条