Name
Title | ||
|---|---|---|
Delay-dependent state estimation for neural networks with state and measurement time-varying delays. |
Abstract | ||
|---|---|---|
This paper deals with the L2–L∞ state estimation for neural networks with time-varying delays. Considering the limited channel capacity or the long transmission time during signal transmission, a new system model with different state and measurement time-varying delays is established. Then, a new Lyapunov–Krasovskii functional (LKF) taking advantage of two types of delay information is constructed, Jensen integral inequality, Wirtinger-based integral inequality and convex combination approach are used to estimate the derivative of functional. Meantime, a novel L2–L∞ performance analysis method making full use of delay information is proposed, as a result, the delay-dependent conditions with less conservatism are obtained, under which the estimation error system is asymptotically stable with a prescribed L2–L∞ performance level. Numerical examples are given to show the effectiveness and the advantage of the proposed method. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1016/j.neucom.2018.11.075 | Neurocomputing |
Keywords | DocType | Volume |
Neural networks,L2–L∞ state estimation,Measurement delay,Lyapunov–Krasovskii functional (LKF) | Journal | 331 |
ISSN | Citations | PageRank |
0925-2312 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wei Qian | 1 | 32 | 12.68 |
| Yujie Li | 2 | 257 | 42.93 |
| Yonggang Chen | 3 | 267 | 20.44 |
| Yi Yang | 4 | 277 | 61.06 |