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The Existence and the Stability of Weighted Pseudo Almost Periodic Solution of High-Order Hopfield Neural Network

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Artificial Neural Networks and Machine Learning – ICANN 2016 (ICANN 2016)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9886))

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Abstract

In this paper, by employing fixed point theorem and differential inequality techniques, some sufficient conditions are given for the existence and the global exponential stability of the unique weighted pseudo almost-periodic solution of high-order Hopfield neural networks with delays. An illustrative example is also given at the end of this paper to show the effectiveness of our results.

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References

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Author information

Authors and Affiliations

  1. Faculty of Sciences of Bizerta, Department of Mathematics, University of Carthage, BP W, Zarzouna, 7021, Bizerta, Tunisia

    Chaouki Aouiti & Mohammed Salah M’hamdi

  2. Laboratory of Math Physics; Specials Functions and Applications LR11ES35, ESSHS, University of Sousse, 4002, Sousse, Tunisia

    Farouk Chérif

Authors
  1. Chaouki Aouiti
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  2. Mohammed Salah M’hamdi
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  3. Farouk Chérif
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Corresponding author

Correspondence to Chaouki Aouiti .

Editor information

Editors and Affiliations

  1. University of Lausanne, Lausanne, Switzerland

    Alessandro E.P. Villa

  2. University of Lausanne, Lausanne, Switzerland

    Paolo Masulli

  3. Universitat Politécnica de Catalunya, Terrrassa, Spain

    Antonio Javier Pons Rivero

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Aouiti, C., M’hamdi, M.S., Chérif, F. (2016). The Existence and the Stability of Weighted Pseudo Almost Periodic Solution of High-Order Hopfield Neural Network. In: Villa, A., Masulli, P., Pons Rivero, A. (eds) Artificial Neural Networks and Machine Learning – ICANN 2016. ICANN 2016. Lecture Notes in Computer Science(), vol 9886. Springer, Cham. https://doi.org/10.1007/978-3-319-44778-0_56

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  • DOI: https://doi.org/10.1007/978-3-319-44778-0_56

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-44777-3

  • Online ISBN: 978-3-319-44778-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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