Singular perturbation analysis of competitive neural networks with different time scales

The dynamics of complex neural networks must include the aspects of long- and short-term memory. The behavior of the network is characterized by an equation of neural activity as a fast phenomenon and an equation of synaptic modification as a slow part of the neural system. The main idea of this pap...

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Veröffentlicht in:	Neural computation Jg. 8; H. 8; S. 1731
Hauptverfasser:	Meyer-Bäse, A, Ohl, F, Scheich, H
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States 15.11.1996
Schlagworte:	Algorithms Models, Neurological Models, Statistical Neural Networks (Computer) Neurons - physiology Probability Time Factors
ISSN:	0899-7667
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Beschreibung
Zusammenfassung:	The dynamics of complex neural networks must include the aspects of long- and short-term memory. The behavior of the network is characterized by an equation of neural activity as a fast phenomenon and an equation of synaptic modification as a slow part of the neural system. The main idea of this paper is to apply a stability analysis method of fixed points of the combined activity and weight dynamics for a special class of competitive neural networks. We present a quadratic-type Lyapunov function for the flow of a competitive neural system with fast and slow dynamic variables as a global stability method and a modality of detecting the local stability behavior around individual equilibrium points.
Bibliographie:	ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 23
ISSN:	0899-7667
DOI:	10.1162/neco.1996.8.8.1731