Exponential Stability Criteria of Fuzzy Cellular Neural Networks with Time-Varying Delays

Author(s):  
Shou-ming Zhong ◽  
Yong-hong Long ◽  
Xing-wen Liu
Author(s):  
Qianhong Zhang ◽  
Lihui Yang ◽  
Daixi Liao

Existence and exponential stability of a periodic solution for fuzzy cellular neural networks with time-varying delays Fuzzy cellular neural networks with time-varying delays are considered. Some sufficient conditions for the existence and exponential stability of periodic solutions are obtained by using the continuation theorem based on the coincidence degree and the differential inequality technique. The sufficient conditions are easy to use in pattern recognition and automatic control. Finally, an example is given to show the feasibility and effectiveness of our methods.


2011 ◽  
Vol 04 (01) ◽  
pp. 55-73
Author(s):  
SHUYUN NIU ◽  
HAIJUN JIANG ◽  
ZHIDONG TENG

In this paper, a class of nonautonomous fuzzy cellular neural networks (FCNNs) with reaction-diffusion terms and time-varying delays are investigated. By applying the inequality analysis technique, introducing ingeniously many real parameters and constructing new auxiliary functions, a series of new and useful criteria on the boundedness and globally exponential stability of solutions are established. The results obtained in this paper extend and improve the corresponding results given in previous works. Finally, two examples are given to verify the effectiveness of the obtained results.


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