Stability of delayed Hopfield neural networks under a sublinear expectation framework

DOI10.1016/j.jfranklin.2018.04.007zbMath1390.93838OpenAlexW2797304858WikidataQ129985267 ScholiaQ129985267MaRDI QIDQ1644282

Litan Yan, Yumiao Li

Publication date: 21 June 2018

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

Full work available at URL: https://doi.org/10.1016/j.jfranklin.2018.04.007

zbMATH Keywords

\(G\)-Brownian motionexponential stability in mean squarestochastic delay Hopfield neural networks

Mathematics Subject Classification ID

Neural networks for/in biological studies, artificial life and related topics (92B20) Asymptotic stability in control theory (93D20) Stochastic stability in control theory (93E15)

Related Items

Delay feedback stabilisation of stochastic differential equations driven by G-Brownian motion ⋮ Delay-dependent asymptotic stability of highly nonlinear stochastic differential delay equations driven by \(G\)-Brownian motion ⋮ Rough path analysis for local time of G-Brownian motion ⋮ Periodic dynamics for nonlocal Hopfield neural networks with random initial data ⋮ Existence and stability of solutions to highly nonlinear stochastic differential delay equations driven by \(G\)-Brownian motion ⋮ Stability analysis of Hopfield neural networks with unbounded delay driven by G-Brownian motion

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