Global asymptotic stability of a class of dynamic neural systems with asymmetric connection weights

被引：0
|
作者：
Xia, YS [1 ]
Wang, J [1 ]
机构：
[1] Chinese Univ Hong Kong, Dept Automat & Comp Aided Engn, Shatin, Hong Kong, Peoples R China
来源：
PROCEEDINGS OF THE 39TH IEEE CONFERENCE ON DECISION AND CONTROL, VOLS 1-5 | 2000年
关键词：
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Recently, a class of dynamic neural systems were presented and analyized due to their good performance in optimization computation and low complexity for implementation. The global asymptotic stability of dynamic neural systems with symmetric weights was well studied. In this paper, we investigate the global asymptotical stability of a dynamic neural system with asymmetric weights. Since asymmetric weight cases are more general than symmetric ones, the new results are significant in both theory and applications.
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页码：870 / 871
页数：2
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