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Stability conditions for Cohen-Grossberg neural networks with time-varying delays. (English) Zbl 1220.93064

Summary: Global asymptotic stability for Cohen-Grossberg neural networks (CGNNs) with time-varying delays is investigated. Criteria are proposed to guarantee the stability and uniqueness of equilibrium point of CGNNs via LMI approach. A numerical example is illustrated to show the effectiveness of our results.

MSC:

93D05 Lyapunov and other classical stabilities (Lagrange, Poisson, \(L^p, l^p\), etc.) in control theory
93D20 Asymptotic stability in control theory
92B20 Neural networks for/in biological studies, artificial life and related topics
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References:

[1] Cohen, M. A.; Grossberg, S., IEEE Trans. Syst. Man. Cybernet., 13, 815 (1983)
[2] Grossberg, S., Neural Networks, 1, 17 (1988)
[3] Cao, J.; Li, X., Physica D, 212, 54 (2005)
[4] Chen, T. P.; Rong, L. B., Phys. Lett. A, 317, 436 (2003)
[5] Liu, J., Chaos Solitons Fractals, 26, 935 (2005)
[6] Wu, W.; Cui, B. T.; Huang, M., Chaos Solitons Fractals, 33, 1355 (2007)
[7] Wu, W.; Cui, B. T.; Huang, M., Chaos Solitons Fractals, 34, 872 (2007)
[8] Boyd, S.; Ghaoui, L. E.; Feron, E.; Balakrishnan, V., Linear Matrix Inequalities in System and Control Theory (1994), SIAM: SIAM Philadelphia · Zbl 0816.93004
[9] Hale, J. K.; Verduyn Lunel, S. M., Introduction to Functional Differential Equations (1993), Springer-Verlag: Springer-Verlag New York · Zbl 0787.34002
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