Name
Abstract | ||
|---|---|---|
This article explores the extended dissipativity conditions for generalised neural networks GNNs including interval time-varying delays. Extended dissipativity criterions are proposed by making proper Lyapunov–Krasovskii functional. The improved reciprocally convex combination and weighted integral inequality techniques are together applied in main results to establish the new extended dissipativity conditions of delayed GNNs. Finally, the feasibility and superiority of the proposed novel approach is clearly shown by numerical examples. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1080/00207721.2017.1316882 | Int. J. Systems Science |
Keywords | Field | DocType |
Generalised neural network, extended dissipativity analysis, time-varying delay, weighted integral inequality | Mathematical optimization,Control theory,Convex combination,Artificial neural network,Mathematics | Journal |
Volume | Issue | ISSN |
48 | 11 | 0020-7721 |
Citations | PageRank | References |
7 | 0.41 | 35 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| R. Saravanakumar | 1 | 231 | 12.70 |
| Grienggrai Rajchakit | 2 | 100 | 11.87 |
| M. Syed Ali | 3 | 518 | 39.49 |
| Young Hoon Joo | 4 | 738 | 76.87 |