Third-order reciprocally convex approach to stability of fuzzy cellular neural networks under impulsive perturbations

2016 ◽  
Vol 21 (3) ◽  
pp. 699-720 ◽  
Author(s):  
Cheng-De Zheng ◽  
Yongjin Xian ◽  
Zhanshan Wang
Keyword(s):  
Neural Networks ◽  
Cellular Neural Networks ◽  
Fuzzy Cellular Neural Networks ◽  
Third Order ◽  
Impulsive Perturbations ◽  
Reciprocally Convex Approach

scholarly journals Existence and exponential stability of a periodic solution for fuzzy cellular neural networks with time-varying delays

2011 ◽  
Vol 21 (4) ◽  
pp. 649-658 ◽  
Author(s):  
Qianhong Zhang ◽  
Lihui Yang ◽  
Daixi Liao
Keyword(s):  
Neural Networks ◽  
Periodic Solution ◽  
Exponential Stability ◽  
Differential Inequality ◽  
Sufficient Conditions ◽  
Coincidence Degree ◽  
Cellular Neural Networks ◽  
Time Varying ◽  
Fuzzy Cellular Neural Networks ◽  
Inequality Technique

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.

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