Novel stability criterions of a new fuzzy cellular neural networks with time-varying delays

  • Authors:

  • Zhenwei Liu;Huaguang Zhang;Zhanshan Wang

  • Affiliations:

  • School of Information Science and Engineering, Northeastern University, Wenhua Road 3-11, Heping District, Shenyang, Liaoning 110004, PR China;School of Information Science and Engineering, Northeastern University, Wenhua Road 3-11, Heping District, Shenyang, Liaoning 110004, PR China;School of Information Science and Engineering, Northeastern University, Wenhua Road 3-11, Heping District, Shenyang, Liaoning 110004, PR China

  • Venue:
  • Neurocomputing
  • Year:
  • 2009

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Abstract

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) 224-233], 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. 4144-4148] and Yuan et al. [Exponential stability and periodic solutions of fuzzy cellular neural networks with time-varying delays, Neurocomputing 69 (13-15) (2006) 1619-1627]. 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.