Bifurcation and Chaos in Delayed Cellular Neural Network Model

Abstract

This paper deals with control of chaotic behavior of a delayed Cellular Neural Network (DCNN) model which is a one-dimensional regular array of four cells with continuous activation function. We investigate different dynamical behaviors including limit cycle, torus, and chaos for different range of weight parameters of the system. Regarding synaptic weight as parameter, Hopf bifurcations are obtained in the system without delay. In the delayed model condition for the Global asymptotic stability of the equilibrium point is presented. Numerical simulation and results are given to show the role of delay in chaos control of the CNNs.

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Das, P. and Kundu, A. (2014) Bifurcation and Chaos in Delayed Cellular Neural Network Model. Journal of Applied Mathematics and Physics, 2, 219-224. doi: 10.4236/jamp.2014.25027.

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1] Chua, L.O. and Yang, L. (1988) Cellular Neural Networks: Theory. IEEE Transactions on Circuits and Systems I, 35, 1257-1272.
[2] Aihara, K., Takabe, T. and Toyoda, M. (1990) Chaotic Neural Networks. Physics Letter A, 6, 333-340. http://dx.doi.org/10.1016/0375-9601(90)90136-C
[3] Pyragas, K. (1992) Continuous Control of Chaos, by Self-Controlling Feedback. Physics Letters A, 170, 421-428. http://dx.doi.org/10.1016/0375-9601(92)90745-8
[4] Wu, J. (2001) Introduction to Neural Dynamics and Signal Transmission Delay. de Gruyter, New York.
[5] Ott, E., Grebogi, C. and Yorke, J.A. (1990) Controlling Chaos. Physical Review Letters, 64, 1196-1199. http://dx.doi.org/10.1103/PhysRevLett.64.1196
[6] Babloyantz, A. and Destexhe, A. (1986) Low-Dimensional Chaos in an Instant of Epilepsy. Proceedings of the National Academy of Sciences of the USA, 83, 3513-3517. http://dx.doi.org/10.1073/pnas.83.10.3513
[7] Freeman, W.J. (1987) Simulation of Chaotic EEG Patterns with a Dynamic Model of the Olfactory System. Biological Cybernetics, 56, 139-150. http://dx.doi.org/10.1007/BF00317988
[8] Jeong, J. and Kim, S.Y. (1997) Nonlinear Analysis of Chaotic Dynamics Underlying the Electroencephalogram in Patients with Alzheimer’s Disease. Journal of the Korean Physical Society, 30, 320-327.
[9] Skarda, C.A. and Freeman, W.J. (1987) How Brains Make Chaos in Order to Make Sense of the World. Behavioral and brain Sc., 19, 161-195.
[10] Skarda, C.A. and Freeman, W.J. (1990) Chaos and the New Science of the Brain. Neuroscience, 1, 275-285.
[11] Chen, L. and Aihara, K. (1999) Global Searching Ability of Chaotic Neural Networks. IEEE Transaction on Circuits and Systems I, 46, 974-993.
[12] Das, A., Roy, A.B. and Das, P. (2002) Chaos in a Three Dimensional General Model of Neural Network. International Journal of Bifurcation and Chaos, 12, 2271-2281. http://dx.doi.org/10.1142/S0218127402005820
[13] Kundu, A., Das, P. and Roy, A.B. (2014) Complex Dynamics of a Four Neuron Network Model Having a Pair of Short-Cut Connections with Multiple Delays. Nonlinear Dynamics, 72, 643-662. http://dx.doi.org/10.1007/s11071-012-0742-2
[14] Yang, X.S. and Huang, Y. (2007) Chaos and Two-Tori in a New Family of 4-CNNs. International Journal of Bifurcation and Chaos, 17, 953-963. http://dx.doi.org/10.1142/S0218127407017677

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