Global Asymptotic Stability and Synchronization of Fractional-Order Reaction–Diffusion Fuzzy BAM Neural Networks with Distributed Delays via Hybrid Feedback Controllers

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dc.contributor.authorSyed Ali, M.
dc.contributor.authorStamov, Gani
dc.contributor.authorStamova, Ivanka
dc.contributor.authorIbrahim, Tarek F.
dc.contributor.authorDawood, Arafa A.
dc.contributor.authorOsman Birkea, Fathea M.
dc.date.accessioned2024-06-28T14:49:54Z
dc.date.available2024-06-28T14:49:54Z
dc.date.issued2023-10-11
dc.date.updated2024-06-28T14:49:55Z
dc.description.abstractIn this paper, the global asymptotic stability and global Mittag–Leffler stability of a class of fractional-order fuzzy bidirectional associative memory (BAM) neural networks with distributed delays is investigated. Necessary conditions are obtained by means of the Lyapunov functional method and inequality techniques. The hybrid feedback controllers are then developed to ensure the global asymptotic synchronization of these neural networks, resulting in two additional synchronization criteria. The derived conditions are applied to check the fractional-order fuzzy BAM neural network’s Mittag–Leffler stability and synchronization. Three examples are given to demonstrate the effectiveness of the achieved results.
dc.identifierdoi: 10.3390/math11204248
dc.identifier.citationMathematics 11 (20): 4248 (2023)
dc.identifier.urihttps://hdl.handle.net/20.500.12588/6440
dc.titleGlobal Asymptotic Stability and Synchronization of Fractional-Order Reaction–Diffusion Fuzzy BAM Neural Networks with Distributed Delays via Hybrid Feedback Controllers

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