Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
412995 | Neurocomputing | 2009 | 7 Pages |
Abstract
In this paper, according to classic MM-matrix method, integral–differential inequality technique and Ito formula, we study asymptotic behavior in mean square sense of stochastic neural networks with infinitely distributed delays by establishing a generalized Halanay inequality. This is a new means for investigating asymptotic behavior of stochastic differential equation. Some useful results are derived. Especially, our methods can be extended to research pp-moment asymptotic behavior easily. At last, example and simulations demonstrate the power of our methods.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Bing Li, Daoyi Xu,