Input-to-state stability analysis for memristive BAM neural networks with variable time delays

DOI10.1016/J.PHYSLETA.2019.01.015zbMath1472.93160OpenAlexW2908947567WikidataQ128578372 ScholiaQ128578372MaRDI QIDQ823543

Lixia Duan, Yong Zhao, Juergen Kurths

Publication date: 24 September 2021

Published in: Physics Letters. A (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.physleta.2019.01.015

zbMATH Keywords

nonsmooth analysisinput-to-state stabilityLyapunov methodmemristive neural networksvariable time delays

Mathematics Subject Classification ID

Input-output approaches in control theory (93D25) Delay control/observation systems (93C43) Networked control (93B70)

Related Items (7)

Finite-time synchronization of memristor-based complex-valued neural networks with time delays ⋮ New results on exponential input-to-state stability analysis of memristor based complex-valued inertial neural networks with proportional and distributed delays ⋮ Stability analysis of stochastic delayed complex networks with multi-weights based on Razumikhin technique and graph theory ⋮ Bifurcations in a fractional-order BAM neural network with four different delays ⋮ Linkage-constraint criteria for robust exponential stability of nonlinear BAM system with derivative contraction coefficients and piecewise constant arguments ⋮ Novel criteria of ISS analysis for delayed memristive simplified Cohen-Grossberg BAM neural networks ⋮ Event-based robust stabilization for delayed systems with parameter uncertainties and exogenous disturbances

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