Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
407940 | Neurocomputing | 2011 | 5 Pages |
Abstract
This paper addresses the analysis problem of asymptotic stability for a class of uncertain neural networks with Markovian jumping parameters and time delays. The considered transition probabilities are assumed to be partially unknown. The parameter uncertainties are considered to be norm-bounded. A sufficient condition for the stability of the addressed neural networks is derived, which is expressed in terms of a set of linear matrix inequalities. A numerical example is given to verify the effectiveness of the developed results.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Y. Lu, W. Ren, S. Yi, Y. Zuo,