 Synchronization for fractional-order discrete-time neural networks with time delaysYajuan Gu, Hu Wang and Yongguang Yu Applied Mathematics and Computation, 2020, vol. 372, issue C Abstract: This paper is concerned with synchronization for fractional-order discrete-time neural networks (FDTNNs) without time delays and with time delays, respectively. First of all, the inequality on Riemann-Liouville fractional difference is proved in the light of the feather of the discrete function A(ν)(k), 0 < ν ≤ 1, which plays an important role in the investigation of the synchronization. Under the feedback controllers, synchronization conditions of FDTNNs without time delays and with time delays are derived by means of different techniques. Based on the inequality and the comparison principle of linear fractional difference system, the synchronization condition of FDTNNs without time delays is obtained. Further more, the synchronization condition of FDTNNs with time delays is derived through Lyapunov direct method with a suitable Lyapunov function involving discrete fractional sum term, which depends on the definition of Riemann-Liouville fractional difference. Lastly, simulations of two examples are provided to prove the effectiveness of the approaches. Keywords: Fractional-order; Synchronization; Time delays; Discrete-time neural networks (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:372:y:2020:i:c:s0096300319309877 DOI: 10.1016/j.amc.2019.124995 Access Statistics for this article Applied Mathematics and Computation is currently edited by Theodore Simos More articles in Applied Mathematics and Computation from Elsevier |
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