On the global robust stability of delayed neural networks

On the global robust stability of delayed neural networks

This paper presents a sufficient condition for the existence, uniqueness and global robust stability of the equilibrium point for Hopfield-type delayed neural networks. The result imposes constraint conditions on the boundary values of the network parameters independently of the delay parameter.

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Bibliographische Detailangaben
Hauptverfasser: Arik, S., Tavsanoglu, V.
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Artificial intelligence
Delay effects
Equations
Hopfield neural networks
Neural networks
Neurons
Robust stability
Stability analysis
Sufficient conditions
Uncertainty
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Beschreibung
Zusammenfassung:This paper presents a sufficient condition for the existence, uniqueness and global robust stability of the equilibrium point for Hopfield-type delayed neural networks. The result imposes constraint conditions on the boundary values of the network parameters independently of the delay parameter.
DOI:10.1109/ISCAS.2002.1010168