Name
Title | ||
|---|---|---|
Global robust stability of general recurrent neural networks with time-varying delays |
Abstract | ||
|---|---|---|
This paper is devoted to global robust stability analysis of the general recurrent neural networks with time-varying parametric uncertainty and time-varying delays. To remove the dependence on the size of time-delays, Lyapunov-Razumikhin stability theorem and LMI approach are applied to derive the global robust stability conditions for the neural networks. Then delay-dependent global robust stability criteria are developed based on integrating Lyapunov-Krasovskii functional method and LMI approach. These stability criteria are in term of the solvability of linear matrix inequalities. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1007/11759966_27 | ISNN (1) |
Keywords | Field | DocType |
global robust stability analysis,lyapunov-razumikhin stability theorem,lyapunov-krasovskii functional method,stability criterion,neural network,general recurrent neural network,lmi approach,delay-dependent global robust stability,global robust stability condition,time-varying delay,linear matrix inequality | Lyapunov function,Control theory,Computer science,Matrix (mathematics),Recurrent neural network,Stability conditions,Parametric statistics,Artificial neural network,Cellular neural network,Linear matrix inequality | Conference |
Volume | ISSN | ISBN |
3971 | 0302-9743 | 3-540-34439-X |
Citations | PageRank | References |
0 | 0.34 | 5 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jun Xu | 1 | 31 | 3.33 |
| Daoying Pi | 2 | 50 | 9.21 |
| Yong-Yan Cao | 3 | 1123 | 106.27 |