American Institute of Mathematical Sciences

Advanced
2003, 2003(Special): 656-663. doi: 10.3934/proc.2003.2003.656

On stochastic stability of dynamic neural models in presence of noise

K Najarian 1,

1. 

College of Information Technology The University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC 28223, United States

Received  September 2002 Revised  March 2003 Published  April 2003

Dynamic feedback neural networks are known to present powerful tools in modeling of complex dynamic models. Since in many real applications, the stability of such models (specially in presence of noise) is of great importance, it is essential to address stochastic stability of such models. In this paper, sufficient conditions for stochastic stability of two families of feedback sigmoid neural networks are presented. These conditions are set on the weights of the networks and can be easily tested.
Keywords: Nonlinear ARX Models., Stochastic Stability, Dynamic Neural Networks.
Mathematics Subject Classification: Primary: 58F15, 58F17, 58F11; Secondary: 53C3.
Citation: K Najarian. On stochastic stability of dynamic neural models in presence of noise. Conference Publications, 2003, 2003 (Special) : 656-663. doi: 10.3934/proc.2003.2003.656
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