Name
Abstract | ||
|---|---|---|
In this brief, the identification problem for time-varying delay nonlinear system is discussed. We use a delayed dynamic neural network to do on-line identification. This neural network has dynamic series-parallel structure. The stability conditions of on-line identification are derived by Lyapunov-Krasovskii approach. The weights of the delayed neural network are updated by the identification error in adaptive method. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/ICNC.2008.539 | ICNC |
Keywords | Field | DocType |
time-varying delay nonlinear system,neural network,identification error,adaptive method,identification problem,identification,delayed neural network,system identification,lyapunov-krasovskii approach,time-varying systems,nonlinear systems,dynamic series-parallel structure,on-line identification,delays,stability condition,stability,delayed dynamic neural network,neural nets,asymptotic stability,artificial neural networks,cellular neural networks,stability analysis,nonlinear system,series parallel | Computer science,Control theory,Stochastic neural network,Nonlinear system identification,Probabilistic neural network,Time delay neural network,Artificial intelligence,Artificial neural network,System identification,Cellular neural network,Parameter identification problem,Machine learning | Conference |
Volume | ISBN | Citations |
3 | 978-0-7695-3304-9 | 0 |
PageRank | References | Authors |
0.34 | 3 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Pu Wang | 1 | 25 | 10.26 |
| Xue li Wu | 2 | 11 | 5.11 |
| Bin Wang | 3 | 0 | 1.01 |
| Jianhua Zhang | 4 | 1 | 1.13 |