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Neural Computation

November 15, 1996, Vol. 8, No. 8, Pages 1731-1742
(doi: 10.1162/neco.1996.8.8.1731)
© 1996 Massachusetts Institute of Technology
Singular Perturbation Analysis of Competitive Neural Networks with Different Time Scales
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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.