Abstract
The exponential stability is analyzed for Cohen-Grossberg neural networks with multiple time-varying delays. The boundedness, differentiability or monotonicity condition is not assumed on the activation functions. Lyapunov functional method is employed to investigate the stability of the neural networks, and general sufficient conditions for the global exponential stability are derived. A numerical example is presented to demonstrate the effectiveness of the obtained criteria.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Chen, T.P., Rong, L.B.: Delay-independent Stability Analysis of Cohen-Grossberg Neural Networks. Physics Letters A 317, 436–449 (2003)
Cohen, M.A., Grossberg, S.: Absolute Stability and Global Pattern Formation and Partial Memory Storage by Competitive Neural Networks. IEEE Transactions on Systems, Man and Cybernetics SMC-13, 815–826 (1983)
Driver, R.D.: Ordinary and Delay Differential Equations. Springer, New York (1977)
van den Driessche, P., Zou, X.: Global Attractivity in Delayed Hopfield Neural Network Models. SIAM J. Appl. Math. 58, 1878–1890 (1998)
Gopalsamy, K., He, X.Z.: Stability in Asymmetric Hopfield Nets with Transmission Delays. Physica D 76, 344–358 (1994)
Grossberg, S.: Nonlinear Neural Networks: Principles, Mechanisms, and Architectures. Neural Networks 1, 17–61 (1988)
Hwang, C.C., Cheng, C.J., Liao, T.L.: Globally Exponential Stability of Generalized Cohen-Grossberg Neural Networks with Delays. Physics Letters A 319(1-2), 157–166 (2003)
Jiang, L.: Global Exponential Stability of Cohen-Grossberg Neural Networks with Time-Varying Delays. Chaos, Solitons and Fractals 26, 935–945 (2005)
Liao, X.F., Li, C.G., Wong, K.W.: Criteria for Exponential Stability of Cohen-Grossberg Neural Networks. Neural Networks 17, 1401–1414 (2004)
Morita, M.: Associative Memory with Non-monotone Dynamics. Neural Networks 6(1), 115–126 (1993)
Peng, J.G., Qiao, H., Xu, Z.B.: A New Approach to Stability of Neural Networks with Time-varying Delays. Neural Networks 15, 95–103 (2002)
Tank, D.W., Hopfield, J.J.: Simple “Neural” Optimization Networks: An A/D Converter, Signal Decision Circuit, and a Linear Programming Circuit. IEEE Transactions on Circuits and Systems 33(5), 533–541 (1986)
Wan, A.H., Mao, W.H., Qiao, H., Zhang, B.: Global Asymptotic Stability of Cohen-Grossberg Neural Networks with Multiple Discrete Delays. In: Huang, D.-S., Heutte, L., Loog, M. (eds.) ICIC 2007. LNCS (LNAI), vol. 4682, pp. 47–58. Springer, Heidelberg (2007)
Wang, L., Zou, X.F.: Exponential Stability of Cohen-Grossberg Neural Networks. Neural Networks 15, 415–422 (2002)
Wang, L., Zou, X.F.: Harmless Delays in Cohen-Grossberg Neural Network. Physica D 170(2), 162–173 (2002)
Wu, W., Cui, B.T., Lou, X.: Some Criteria for Asymptotic Stability of Cohen-Grossberg Neural Networks with Time-Varying Delays. Neurocomputing 70(4-6), 1085–1088 (2007)
Ye, H., Michel, A.N., Wang, K.: Qualitative Analysis of Cohen-Grossberg Neural Networks with Multiple Delays. Physics Review E 51, 2611–2618 (1995)
Zhang, Y., Tan, K.K.: Dynamic Stability for Lotka-Volterra Recurrent Neural Networks with Delays. Physical Review E 66, 011910 (2002)
Zhou, D.M., Cao, J.D.: Globally Exponential Stability Conditions for Cellular Neural Networks with Time-Varying Delays. Applied Mathematics and Computation 131(2-3), 487–496 (2002)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Wan, A., Mao, W. (2008). Criteria for Exponential Stability of Cohen-Grossberg Neural Networks with Multiple Time-Varying Delays. In: Huang, DS., Wunsch, D.C., Levine, D.S., Jo, KH. (eds) Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence. ICIC 2008. Lecture Notes in Computer Science(), vol 5227. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85984-0_3
Download citation
DOI: https://doi.org/10.1007/978-3-540-85984-0_3
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-85983-3
Online ISBN: 978-3-540-85984-0
eBook Packages: Computer ScienceComputer Science (R0)