Global robust stability of competitive neural networks with continuously distributed delays and different time scales

Authors:
Yonggui Kao;QingHe Ming
Affiliations:
Department of Mathematics, ZaoZhuang University, People's Republic of China;Department of Mathematics, ZaoZhuang University, People's Republic of China
Venue:
ICANN'07 Proceedings of the 17th international conference on Artificial neural networks
Year:
2007

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Abstract

The dynamics of cortical cognitive maps developed by selforganization must include the aspects of long and short-term memory. The behavior of such a neural 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, besides, this model bases on unsupervised synaptic learning algorithm. In this paper, using theory of the topological degree and strict Liapunov functional methods, we prove existence and uniqueness of the equilibrium of competitive neural networks with continuously distributed delays and different time scales, and present some new criteria for its global robust stability.