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This article is cited in 3 scientific papers (total 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.
Received: 15.07.2021 Revised: 15.07.2021 Accepted: 29.09.2021
Citation:
M. Es-saiydy, M. Zitane, “Dynamic behavior of a class of delayed Lotka–Volterra recurrent neural networks on time scales”, Izv. Vyssh. Uchebn. Zaved. Mat., 2021, no. 11, 67–85; Russian Math. (Iz. VUZ), 65:11 (2021), 59–75
Linking options:
https://www.mathnet.ru/eng/ivm9730 https://www.mathnet.ru/eng/ivm/y2021/i11/p67
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Abstract page: | 86 | Full-text PDF : | 31 | References: | 13 | First page: | 4 |
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