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JOURNALS // Izvestiya Vysshikh Uchebnykh Zavedenii. Matematika // Archive

Izv. Vyssh. Uchebn. Zaved. Mat., 2021 Number 11, Pages 67–85 (Mi ivm9730)

This article is cited in 3 papers

Dynamic behavior of a class of delayed Lotka–Volterra recurrent neural networks on time scales

M. Es-saiydy, M. Zitane

Moulay Ismaïl University Meknès, Morocco

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.

Keywords: time scale, Bochner-like transform, Lotka-Volterra recurrent neural network, weighted Stepanov-like pseudo almost periodic solution, global stability.

UDC: 517

Received: 15.07.2021
Revised: 15.07.2021
Accepted: 29.09.2021

DOI: 10.26907/0021-3446-2021-11-67-85


 English version:
Russian Mathematics (Izvestiya VUZ. Matematika), 2021, 65:11, 59–75


© Steklov Math. Inst. of RAS, 2024