Existence and exponential stability of almost periodic solution for Hopfield-type neural networks with impulse

DOI10.1016/j.chaos.2006.09.085zbMath1155.34323OpenAlexW2087971799MaRDI QIDQ937322

Huiying Zhang, Yong-Hui Xia

Publication date: 14 August 2008

Published in: Chaos, Solitons and Fractals (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.chaos.2006.09.085

zbMATH Keywords

almost periodic solutionsHopfield-type neural networks with impulses

Mathematics Subject Classification ID

Neural networks for/in biological studies, artificial life and related topics (92B20) Ordinary differential equations with impulses (34A37) Stability of solutions to ordinary differential equations (34D20) Almost and pseudo-almost periodic solutions to ordinary differential equations (34C27)

Related Items (9)

Global exponential stability of high-order Hopfield neural networks with state-dependent impulses ⋮ New results for global robust stability of bidirectional associative memory neural networks with multiple time delays ⋮ Existence and exponential stability of almost periodic solution for stochastic cellular neural networks with delay ⋮ The measure pseudo almost-periodicty and automorphy in HOHNNs with time-varying delays ⋮ Dynamic behaviors of a class of memristor-based Hopfield networks ⋮ Robust stability analysis of fractional-order Hopfield neural networks with parameter uncertainties ⋮ Almost periodic solutions for systems with delay and nonfixed times of impulsive actions ⋮ Dynamics of impulsive neutral-type BAM neural networks ⋮ A new sufficient condition for global robust stability of bidirectional associative memory neural networks with multiple time delays

Cites Work

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• New results on the existence and uniqueness of almost periodic solution for BAM neural networks with continuously distributed delays
• Existence and exponential stability of almost periodic solution for shunting inhibitory cellular neural networks with impulses
• The existence of almost periodic solutions of certain perturbation systems
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