Global asymptotic stability of high-order delay Hopfield neural networks with time-varying coefficients

DOI10.4171/ZAA/1249zbMath1106.34050OpenAlexW1968916389MaRDI QIDQ816283

Peiguang Wang, Hairong Lian, Yong-Hong Wu

Publication date: 10 March 2006

Published in: Zeitschrift für Analysis und ihre Anwendungen (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.4171/zaa/1249

zbMATH Keywords

neural networksLyapunov functionalglobal asymptotic stability

Mathematics Subject Classification ID

Neural networks for/in biological studies, artificial life and related topics (92B20) Asymptotic theory of functional-differential equations (34K25) Stability theory of functional-differential equations (34K20)

Related Items (5)

Stability and synchronization of a fractional neutral higher-order neural network system ⋮ Existence and exponential stability of positive almost periodic solutions for high-order Hopfield neural networks ⋮ Exponential convergence for high-order recurrent neural networks with a class of general activation functions ⋮ Existence and exponential stability of almost-periodic solutions for high-order Hopfield neural networks ⋮ Learning dynamics in second order networks

Cites Work

• Theory of functional differential equations. 2nd ed
• On the global convergence of a class of functional differential equations with applications in neural network theory
• On global asymptotic stability of a class of nonlinear systems arising in neural network theory
• Stability in asymmetric Hopfield nets with transmission delays
• Stability analysis of delayed neural networks
• High-order absolutely stable neural networks

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