Exponential stability for cellular neural networks with delay

被引：0
|
作者：
Yang, Jinxiang [1 ]
Zhong, Shouming [2 ]
Liu, Xingwen [3 ]
机构：
[1] Southwest Univ Nationalities, Coll Comp Sci & Technol, Chengdu 610041, Peoples R China
[2] Univ Elect & Technol China, Sch Appl Math, Chengdu 610054, Peoples R China
[3] Southwest Univ Natl, Coll Elect Informat Engn, Chengdu 610041, Peoples R China
来源：
2006 13TH IEEE INTERNATIONAL CONFERENCE ON ELECTRONICS, CIRCUITS AND SYSTEMS, VOLS 1-3 | 2006年
关键词：
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
This paper investigates the exponential stability of a class of delayed cellular neural networks (DCNN's). By means of appropriately dividing the network state variables into several subgroups, the new sufficient exponential stability condition is derived by constructing Liapunov functional and using the method of the variation of constant. The condition suitable is associated with some initial values and is represented only by some blocks of the interconnection matrix. An example is discussed to illustrate the results.
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页码：930 / +
页数：2
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