Global exponential stability of discrete-time higher-order Cohen-Grossberg neural networks with time-varying delays, connection weights and impulses
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Publication:2041437
DOI10.1016/j.jfranklin.2021.05.020zbMath1467.93266OpenAlexW3164170657WikidataQ115570666 ScholiaQ115570666MaRDI QIDQ2041437
Xian Zhang, Xin Wang, Zeyu Dong
Publication date: 19 July 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.2021.05.020
Discrete-time control/observation systems (93C55) Exponential stability (93D23) Networked control (93B70)
Related Items (7)
Global exponential stability of discrete-time Hopfield neural network models with unbounded delays ⋮ Algebra criteria for global exponential stability of multiple time-varying delay Cohen-Grossberg neural networks ⋮ Delayed impulsive control for lag synchronization of neural networks with time-varying delays and partial unmeasured states ⋮ Global exponential p-norm stability of BAM neural networks with unbounded time-varying delays: A method based on the representation of solutions ⋮ Laplace transform and nonlinear control design for quasi‐projective synchronization for Caputo inertial delayed neural networks ⋮ Novel criteria for robust stability of Cohen-Grossberg neural networks with multiple time delays ⋮ Stability analysis of hybrid stochastic delayed Cohen-Grossberg neural networks with Lévy noise and Markov switching
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