Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
405692 | Neurocomputing | 2016 | 9 Pages |
Abstract
This paper is concerned with the input-to-state stability problem of a class of neutral stochastic neural networks. The stochastic neural networks that we consider contain both neutral terms and mixed delays. By utilizing the Lyapunov–Krasovskii functional method, stochastic analysis techniques and It o^׳s formula, some sufficient conditions are derived to ensure the mean-square exponential input-to-state stability of the addressed system. Two numerical examples and their simulations are given to illustrate the effectiveness of the derived results.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Yinfang Song, Wen Sun, Feng Jiang,