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Exponential Lag Synchronization for Delayed Cohen-Grossberg Neural Networks with Discontinuous Activations

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Abstract

In this paper, we investigate the exponential lag synchronization of delayed Cohen-Grossberg neural networks with discontinuous activation functions. By employing the analysis technique and theory of the differential equations with discontinuous right-hand side, some novel lag synchronization criteria have been obtained. Finally, an example is given to illustrate the effectiveness of the obtained results.

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Author information

Authors and Affiliations

  1. College of Mathematics and System Sciences, Xinjiang University, Urumqi, 830046, Xinjiang, P.R. China

    Abdujelil Abdurahman, Cheng Hu & Haijun Jiang

Authors
  1. Abdujelil Abdurahman
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  2. Cheng Hu
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  3. Haijun Jiang
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Technology, Tsinghua University, Beijing, China

    Xiaolin Hu

  2. Fuzhou University, Fuzhou, China

    Yousheng Xia

  3. School of Information Science and Technology, Sun Yat-sen University, Guangzhou, China

    Yunong Zhang

  4. Chinese Academy of Sciences, Institute of Automation, Beijing, China

    Dongbin Zhao

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© 2015 Springer International Publishing Switzerland

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Abdurahman, A., Hu, C., Jiang, H. (2015). Exponential Lag Synchronization for Delayed Cohen-Grossberg Neural Networks with Discontinuous Activations. In: Hu, X., Xia, Y., Zhang, Y., Zhao, D. (eds) Advances in Neural Networks – ISNN 2015. ISNN 2015. Lecture Notes in Computer Science(), vol 9377. Springer, Cham. https://doi.org/10.1007/978-3-319-25393-0_15

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  • DOI: https://doi.org/10.1007/978-3-319-25393-0_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-25392-3

  • Online ISBN: 978-3-319-25393-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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