Exponential Stability of Fuzzy Cellular Neural Networks with Unbounded Delay

Author(s):  
Tingwen Huang ◽  
Linhua Zhang
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.


2009 ◽  
Vol 19 (10) ◽  
pp. 3387-3395 ◽  
Author(s):  
LIPING CHEN ◽  
RANCHAO WU

The exponential stability of a class of stochastic fuzzy cellular neural networks with distributed delays is investigated in this paper. By using analytic methods such as Lyapunov functional, Itô's formula, inequality techniques and non-negative semimartingale convergence theorem, the sufficient conditions guaranteeing the almost sure and mean square exponential stability of its equilibrium solution are respectively obtained. For illustration, an example is given to show the feasibility of results.


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