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Algebraic condition of synchronization for multiple time-delayed chaotic Hopfield neural networks

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Abstract

In this paper, an easy and efficient method is brought forward to design the feedback control for the synchronization of two multiple time-delayed chaotic Hopfield neural networks, whose activation functions and delayed activation functions can have different forms of mapping. Without many complex restrictions and Lyapunov analytic process, the feedback control is given based on the M-matrix theory, the system parameters and the feedback section coefficients. All the results are simulated by Matlab and Simulink, which shows the simplicity and validity of the control. As shown in the simulation results, the error systems converge to zero rapidly.

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Acknowledgments

This work was supported by the National Natural Science Foundation of China under Grant 60974136 and 60774029.

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Authors and Affiliations

  1. College of Science, Naval University of Engineering, 430033, Wuhan, China

    Hanlin He & Jianjun Tu

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  1. Hanlin He
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  2. Jianjun Tu
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Correspondence to Hanlin He.

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He, H., Tu, J. Algebraic condition of synchronization for multiple time-delayed chaotic Hopfield neural networks. Neural Comput & Applic 19, 543–548 (2010). https://doi.org/10.1007/s00521-009-0306-7

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