Name
Title | ||
|---|---|---|
Less conservative results of state estimation for neural networks with time-varying delay |
Abstract | ||
|---|---|---|
In this paper, the state estimation problem is investigated for continuous-time neural networks with time-varying delay through available output measurements. By constructing more effective Lyapunov functionals, and combining with Jensen integral inequality or free-weighting matrix approach, several less conservative sufficient conditions for the existence of state estimator are derived in terms of linear matrix inequalities (LMIs). Finally, a numerical example is presented to demonstrate the effectiveness and the reduced conservatism of proposed results. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1016/j.neucom.2009.12.019 | Neurocomputing |
Keywords | Field | DocType |
effective lyapunov functionals,jensen integral inequality,matrix approach,conservative result,linear matrix inequality,numerical example,continuous-time neural network,available output measurement,state estimator,state estimation problem,conservative sufficient condition,time-varying delay,neural network,lyapunov function,neural networks | Mathematical optimization,State estimator,Matrix (mathematics),Conservatism,Artificial neural network,Jensen integral inequality,Lyapunov functionals,Mathematics | Journal |
Volume | Issue | ISSN |
73 | 7-9 | Neurocomputing |
Citations | PageRank | References |
12 | 0.63 | 19 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yonggang Chen | 1 | 267 | 20.44 |
| Weiping Bi | 2 | 57 | 3.56 |
| Wenlin Li | 3 | 104 | 6.69 |
| Yuanyuan wu | 4 | 126 | 9.00 |