Abstract
In this paper, based on the ideas of T-S fuzzy, the T-S fuzzy Cohen-Grossberg neural network model with mixed time-varying is presented. By using Lyapunov functional approach, some sufficient conditions are obtained to guarantee the T-S fuzzy Cohen-Grossberg neural networks to be globally asymptotically stable for all admissible parametric uncertainties. A numerical example is provided to illustrate the usefulness of the theoretical result.
This work was supported by the Natural Science Foundation of Hebei Province of China (A2011203103) and the Hebei Province Education Foundation of China (2009157).
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References
Cohen, M.A., Grossberg, S.: Absolute stability and global pattern formation and parallel memory storage by competitive neural networks. IEEE Trans. Syst., Man, Cybern. 13, 815–826 (1983)
Lu, K., Xu, D., Yang, Z.: Global attraction and stability for Cohen-Grossberg neural networks with time delays. Neural Netw. 19, 1538–1549 (2006)
Yuan, K., Cao, J.: An analysis of global asymptotic stability of delayed Cohen–Grossberg neural networks via nonsmooth analysis. IEEE Trans. Circuits Syst. I, Reg. Papers 52, 1854–1861 (2005)
Huang, H., Qu, Y., Li, H.: Robust stability analysis of switched Hopfield neural networks with time-varying delay under uncertainty. Phys. Lett. A 345, 345–354 (2005)
Lu, W., Chen, T.: New conditions on global stability of Cohen–Grossberg neural networks. Neural Comput. 15, 1173–1189 (2003)
Cao, J., Song, Q.: Stability in Cohen-Grossberg type BAM neural networks with time-varying delays. Nonlinearity 19, 1601–1617 (2006)
Cao, J., Li, X.: Stability in delayed Cohen–Grossberg neural networks. LMI Optimization Approach Physica D 54–65 (2005)
Li, T., Fei, S., Guo, Y., Zhu, Q.: Stability analysis on Cohen-Grossberg neural networks with both time-varying and continuously distributed delays. Nonlinear Anal., Real Word Appl. 10, 2600–2612 (2009)
Huang, T.W.: Exponential stability of fuzzy cellular neural networks with distributed delay. Phys. Lett. A 351, 48–52 (2006)
Zhang, Y., Heng, P.A.: Stability of fuzzy control systems with bounded uncertain delays. IEEE Trans. Fuzzy Systems 10, 92–97 (2002)
Lou, X., Cui, B.: Robust asymptotic stability of uncertain fuzzy BAM neural networks with time-varying delays. Fuzzy Sets and Systems 158, 2746–2756 (2007)
Boyd, S., El Ghaoui, L., Feron, E., Balakrishnan, V.: Linear Matrix Inequalities in System and Control Theory. SIAM, Philadephia (1994)
Gu, K., Kharitonov, V., Chen, J.: Stability of Time-Delay Systems. Birkhäuser, Boston (2003)
Xie, L.: Output feedback H∞ control of systems with parameter uncertainty. Int. J. Control 63, 741–750 (1996)
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Wang, Y., Liu, D. (2012). Robust Stability Analysis of Fuzzy Cohen-Grossberg Neural Networks with Mixed Time-Varying Delay. In: Wang, J., Yen, G.G., Polycarpou, M.M. (eds) Advances in Neural Networks – ISNN 2012. ISNN 2012. Lecture Notes in Computer Science, vol 7367. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31346-2_39
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DOI: https://doi.org/10.1007/978-3-642-31346-2_39
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