Global asymptotic stability for a linear system in a saturated mode

DOI10.1016/S0167-6911(99)00117-6zbMath0977.93071WikidataQ126977318 ScholiaQ126977318MaRDI QIDQ1575292

Bruce D. Calvert

Publication date: 21 August 2000

Published in: Systems \& Control Letters (Search for Journal in Brave)

zbMATH Keywords

optimizationglobal asymptotic stabilitymatrix measureneural netequilibrium pointaccretiveHopfield net model

Mathematics Subject Classification ID

Numerical optimization and variational techniques (65K10) Neural networks for/in biological studies, artificial life and related topics (92B20) Asymptotic stability in control theory (93D20)

Related Items (1)

Neural networks with an infinite number of cells

Cites Work

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• Global asymptotic stability of a class of feedback neural networks with an application to optimization problems
• Asymptotic stability of systems operating on a closed hypercube
• On the global convergence of a class of functional differential equations with applications in neural network theory
• Linear systems in a saturated mode and convergence as gain becomes large of asymptotically stable equilibrium points of neural nets
• A sufficient condition for absolute stability of a larger class of dynamical neural networks
• Analysis and synthesis of a class of neural networks: linear systems operating on a closed hypercube
• Global Attractivity in Delayed Hopfield Neural Network Models
• On the dynamic behaviour of two‐cell cellular neural networks
• Global convergence of the Hopfield neural network with nonzero diagonal elements

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