Name
Title | ||
|---|---|---|
Robust extended dissipativity criteria for discrete-time uncertain neural networks with time-varying delays. |
Abstract | ||
|---|---|---|
In this draft, we consider the problem of robust extended dissipativity for uncertain discrete-time neural networks (DNNs) with time-varying delays. By constructing appropriate Lyapunov–Krasovskii functional (LKF), sufficient conditions are established to ensure that the considered time-delayed uncertain DNN is extended dissipative. The derived conditions are presented in terms of linear matrix inequalities (LMIs). Numerical examples are provided to illustrate the superiority of this result. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1007/s00521-017-2974-z | Neural Computing and Applications |
Keywords | Field | DocType |
Extended dissipativity analysis, Uncertain discrete-time neural networks, Lyapunov method, Linear matrix inequality | Mathematical optimization,Matrix (mathematics),Dissipative system,Artificial intelligence,Discrete time and continuous time,Artificial neural network,Mathematics,Linear matrix inequality,Machine learning | Journal |
Volume | Issue | ISSN |
30 | 12 | 0941-0643 |
Citations | PageRank | References |
5 | 0.39 | 30 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| R. Saravanakumar | 1 | 231 | 12.70 |
| Grienggrai Rajchakit | 2 | 100 | 11.87 |
| M. Syed Ali | 3 | 518 | 39.49 |
| Zhengrong Xiang | 4 | 302 | 31.42 |
| Young Hoon Joo | 5 | 738 | 76.87 |