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Dynamic Behavior of a Class of Delayed Lotka–Volterra Recurrent Neural Networks on Time Scales

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Abstract

In this paper, Lotka–Volterra recurrent neural networks with time-varying delays on time scales are considered. Using Banach's fixed-point principle, the theory of calculus on time scales and suitable Lyapunov functional, some sufficient conditions for the existence, uniqueness and Stepanov-exponential stability of positive weighted Stepanov-like pseudo almost periodic solution on time scales to the recurrent neural networks are established. Finally, an illustrative example and simulations are presented to demonstrate the effectiveness of the theoretical findings of the paper. The results of this paper are new and generalize some previously-reported results in the literature.

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Authors and Affiliations

  1. Moulay Ismaïl University, Faculty of Sciences, Department of Mathematics, MACS Laboratory, Meknès, Morocco

    M. Es-saiydy & M. Zitane

Authors
  1. M. Es-saiydy
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  2. M. Zitane
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Correspondence to M. Es-saiydy or M. Zitane.

Additional information

Russian Text © The Author(s), 2021, published in Izvestiya Vysshikh Uchebnykh Zavedenii. Matematika, 2021, No. 11, pp. 67–85.

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Es-saiydy, M., Zitane, M. Dynamic Behavior of a Class of Delayed Lotka–Volterra Recurrent Neural Networks on Time Scales. Russ Math. 65, 59–75 (2021). https://doi.org/10.3103/S1066369X21110074

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