Global Exponential Stability of Fuzzy Cellular Neural Networks with Impulses and Infinite Delays
Received:March 11, 2006  Revised:October 10, 2006
Key Words: global exponential stability   fuzzy cellular neural networks   impulses   infinite delays   integro-differential inequality.  
Fund Project:the National Natural Science Foundation of China (No. 10671133); the Doctors' Foundation of Chongqing University of Posts and Telecommunication (No. A2007-41).
Author NameAffiliation
ZHU Wei Institute of Applied Mathematics, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
Yangtze Center of Mathematics, Sichuan University, Sichuan 610064, China 
XU Dao-yi Yangtze Center of Mathematics, Sichuan University, Sichuan 610064, China 
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Abstract:
      In this paper, the global exponential stability of fuzzy cellular neural networks with impulses and infinite delays is investigated. Based on an impulsive delayed integro-differential inequality and the properties of fuzzy logic operation and M-matrix, an easily verified sufficient condition is obtained. Moreover, the exponential convergent rate for the fuzzy cellular neural networks with impulses and infinite delays is also given. An example is given to illustrate the effectiveness of our theoretical result.
Citation:
DOI:10.3770/j.issn:1000-341X.2008.01.001
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