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New Results for Impulsive Recurrent Neural Networks with Time-Varying Coefficients and Mixed Delays

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Abstract

In this paper, we shall explain a new result concerning piecewise weighted pseudo almost-periodic solution of impulsive recurrent neural networks with time-varying coefficients and mixed delays. Precisely, some sufficient conditions are given to prove the existence and the exponential stability of piecewise weighted pseudo almost-periodic solution by employing fixed point theorem, generalized Gronwall–Bellman inequality and differential inequality techniques. Finally, an illustrative example is given to demonstrate the effectiveness of our results.

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Authors and Affiliations

  1. University of Carthage, Faculty of Sciences of Bizerta, Department of Mathematics, Research Units of Mathematics and Applications UR13ES47, 7021, Zarzouna, Bizerta, Tunisia

    Chaouki Aouiti & Mohammed Salah M’hamdi

  2. Department of Computer Science, ISSATS, Laboratory of Math Physics, Specials Functions and Applications LR11ES35, 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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Correspondence to Chaouki Aouiti.

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Aouiti, C., M’hamdi, M.S. & Chérif, F. New Results for Impulsive Recurrent Neural Networks with Time-Varying Coefficients and Mixed Delays. Neural Process Lett 46, 487–506 (2017). https://doi.org/10.1007/s11063-017-9601-y

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