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Qianhong Zhang, Yuanfu Shao and Jingzhong Liu

Abstract

In this paper, by applying the method of coincidence degree, M-matrix theory and constructing some suitable Lyapunov functional, some sufficient conditions are established for the existence and global exponential stability of periodic solutions for a kind of impulsive fuzzy cellular neural networks with mixed delays on time scales. Without assuming the boundedness of the activation functions fj ; gj , these results are less restrictive than those given in the earlier references. Moreover an example is given to illustrate our results.

Open access

Qianhong Zhang, Lihui Yang and 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.

Open access

Qianhong Zhang, Jingzhong Liu and Yuanfu Shao

Abstract

By applying the method of coincidence degree and constructing a suitable Lyapunov functional, some sufficient conditions are established for the existence and globally exponential stability of periodic solutions for a kind of impulsive fuzzy Cohen- Grossberg neural networks on time scales. Moreover an example is given to illustrate our results.