| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 4634462 | Applied Mathematics and Computation | 2008 | 8 Pages |
Abstract
The global asymptotic stability of stochastic recurrent neural networks with time varying delays is analyzed. In this paper, by utilizing the Lyapunov functional and combining with the linear matrix inequality (LMI) approach, we analyze the global asymptotic stability of stochastic delayed recurrent neural networks. In addition, an example is also provided to illustrate the applicability of the result.
Keywords
Related Topics
Physical Sciences and Engineering
Mathematics
Applied Mathematics
Authors
R. Rakkiyappan, P. Balasubramaniam,