Pinning multisynchronization of delayed fractional-order memristor-based neural networks with nonlinear coupling and almost-periodic perturbations

DOI10.1016/j.neunet.2021.08.029zbMath1526.93249OpenAlexW3196813293MaRDI QIDQ6055148

Xifeng Li, Dongjie Bi, Xuan Xie, Libiao Peng, Yongle Xie

Publication date: 28 September 2023

Published in: Neural Networks (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.neunet.2021.08.029

zbMATH Keywords

multistabilityalmost periodicitynonlinear couplingmultisynchronizationfractional-order memristor-based neural networks

Mathematics Subject Classification ID

Perturbations in control/observation systems (93C73) Fractional derivatives and integrals (26A33) Stability of control systems (93D99) Delay control/observation systems (93C43) Networked control (93B70)

Related Items (3)

Novel results on asymptotic stability and synchronization of fractional-order memristive neural networks with time delays: the \(0<\delta\leq 1\) case ⋮ Function matrix projection synchronization for the multi-time delayed fractional order memristor-based neural networks with parameter uncertainty ⋮ Sampled-data-based exponential synchronization of switched coupled neural networks with unbounded delay

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