Global exponential stability of discrete-time recurrent neural networks with impulses

DOI10.1016/j.na.2009.06.108zbMath1239.39015OpenAlexW2027425012MaRDI QIDQ425914

Xinquan Zhao

Publication date: 9 June 2012

Published in: Nonlinear Analysis. Theory, Methods \& Applications. Series A: Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.na.2009.06.108

zbMATH Keywords

unique equilibriumglobally exponential stabilitydiscrete-time recurrent neural networks

Mathematics Subject Classification ID

Neural networks for/in biological studies, artificial life and related topics (92B20) Discrete-time control/observation systems (93C55) Asymptotic stability in control theory (93D20) Stability theory for difference equations (39A30)

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Global exponential stability of neural networks with non-smooth and impact activations ⋮ About the stabilization of a nonlinear perturbed difference equation

Cites Work

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• Continuous-time additive Hopfield-type neural networks with impulses.
• Turbulence in Multistep Methods for Initial Value Problems
• Comments on "Necessary and sufficient condition for absolute stability of neural networks"

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