Novel stability criterions of a new fuzzy cellular neural networks with time-varying delays ?
Global exponential stability problem of a class of new fuzzy cellular neural networks with time-varying delays is investigated. Novel delay-dependent stability criterions based on Lyapunov stability theory and linear matrix inequality technique are derived. Compared with previous results, the signs of elements of weight matrices of the non-fuzzy terms is considered. Thus, the obtained criterions are less conservative than the results in Liu and Tang [Exponential stability of fuzzy cellular neural networks with constant and time-varying delays, Phys. Lett. A 323 (3/4) (2004) 224233], Zhong et al. [Exponential stability criteria of fuzzy cellular neural networks with time-varying delays, in: Proceedings of the International Conference on Machine Learning and Cybernetics, 2006, pp. 41444148] and Yuan et al. [Exponential stability and periodic solutions of fuzzy cellular neural networks with time-varying delays, Neurocomputing 69 (1315) (2006) 16191627]. Moreover, the restriction on the change rate of time-varying delays is relaxed in the proposed criterions. Two examples are provided to verify the effectiveness of the proposed results.
fuzzy cellular neural networks time-varying delays global exponential stability delay-dependent linear matrix inequality (lmi)