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Pseudo Almost Automorphic Solutions of Recurrent Neural Networks with Time-Varying Coefficients and Mixed Delays

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Abstract

In this paper, existence, uniqueness and global exponential stability of pseudo almost automorphic solutions for a class of recurrent neural networks with time-varying coefficients and mixed delays are established by employing the fixed point theorem and differential inequality. Numerical example with graphical illustration is given to illuminate our main results.

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Authors and Affiliations

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

    Chaouki Aouiti, Mohammed Salah M’hamdi & Abderrahmane Touati

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  1. Chaouki Aouiti
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  2. Mohammed Salah M’hamdi
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  3. Abderrahmane Touati
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Correspondence to Chaouki Aouiti.

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Aouiti, C., M’hamdi, M.S. & Touati, A. Pseudo Almost Automorphic Solutions of Recurrent Neural Networks with Time-Varying Coefficients and Mixed Delays. Neural Process Lett 45, 121–140 (2017). https://doi.org/10.1007/s11063-016-9515-0

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  • DOI: https://doi.org/10.1007/s11063-016-9515-0

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