Quasi-synchronization of coupled neural networks with reaction-diffusion terms driven by fractional Brownian motion

DOI10.1016/j.jfranklin.2021.01.023zbMath1459.93062OpenAlexW3121304094MaRDI QIDQ2656853

Shuai Song, Yijun Zhang, Xiaona Song, Xingru Li, Zhaoke Ning

Publication date: 16 March 2021

Published in: Journal of the Franklin Institute (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jfranklin.2021.01.023

zbMATH Keywords

fractional Brownian motionsampled-data controlreaction-diffusion neural networksquasi-synchronization

Mathematics Subject Classification ID

Fractional processes, including fractional Brownian motion (60G22) Control/observation systems governed by partial differential equations (93C20) Reaction-diffusion equations (35K57) Sampled-data control/observation systems (93C57) Networked control (93B70)

Related Items (8)

Robust synchronization of uncertain Markovian jumping complex interconnected neural networks via adaptive fault-tolerant control ⋮ General decay anti-synchronization and \(H_\infty\) anti-synchronization of coupled reaction-diffusion complex-valued memristive neural networks ⋮ Quasi-synchronization of heterogeneous stochastic coupled reaction-diffusion neural networks with mixed time-varying delays via boundary control ⋮ Global synchronization for BAM delayed reaction-diffusion neural networks with fractional partial differential operator ⋮ Synchronization for multiweighted and directly coupled reaction-diffusion neural networks with hybrid coupling via boundary control ⋮ Synchronization of fractional-order spatiotemporal complex-valued neural networks in finite-time interval and its application ⋮ Adaptive quantitative exponential synchronization in multiplex Cohen-Grossberg neural networks under deception attacks ⋮ Two boundary coupling approaches for synchronization of stochastic reaction-diffusion neural networks based on semi-linear PIDEs

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