Name
Title | ||
|---|---|---|
Robust stability of uncertain Markovian jump discrete-time recurrent neural networks with time delays |
Abstract | ||
|---|---|---|
This article is concerned with robust stochastic stability for a class of uncertain Markovian jump discrete-time recurrent neural networks (MJDRNNs) with time delays. The uncertainty is assumed to be of the norm-bounded form. By employing the Lyapunov functional and linear matrix inequality (LMI) approach, some sufficient criteria are proposed for the robust stochastic stability in the mean square of the MJDRNNs with constant or mode-dependent time delays. The proposed LMI-based results are computationally efficient as they can be solved numerically using standard commercial software. The validity of the obtained results are further illustrated by two simulation examples. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1080/00207720903431785 | Int. J. Systems Science |
Keywords | Field | DocType |
norm-bounded form,robust stochastic stability,robust stability,mean square,linear matrix inequality,uncertain markovian jump discrete-time,mode-dependent time delay,recurrent neural network,time delay,standard commercial software,proposed lmi-based result,simulation example,neural network,lyapunov function,discrete time | Lyapunov function,Control theory,Recurrent neural network,Robustness (computer science),Discrete time and continuous time,Robust control,Artificial neural network,Linear matrix inequality,Jump process,Mathematics | Journal |
Volume | Issue | ISSN |
41 | 12 | 0020-7721 |
Citations | PageRank | References |
6 | 0.45 | 15 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ming Gao | 1 | 79 | 8.36 |
| Li Sheng | 2 | 125 | 15.24 |
| Baotong Cui | 3 | 339 | 39.97 |