Name
Title | ||
|---|---|---|
Asymptotic synchronization for stochastic memristor-based neural networks with noise disturbance. |
Abstract | ||
|---|---|---|
In this paper, globally asymptotical synchronization for stochastic memristor-based neural networks with random noise disturbance is investigated. Under the framework of differential inclusions theory and set-valued maps, a state feedback controller and an adaptive updated law are designed by constructing a suitable Lyapunov functional. By using Itô formula and some significant inequality techniques, sufficient conditions for the global synchronization of the stochastic memristor-based neural networks which are more general are obtained. Finally, numerical simulations are provided to illustrate the theoretical results. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1016/j.jfranklin.2016.06.002 | Journal of the Franklin Institute |
Field | DocType | Volume |
Differential inclusion,Synchronization,Memristor,Full state feedback,Control theory,Random noise,Stochastic neural network,Artificial neural network,Noise pollution,Mathematics | Journal | 353 |
Issue | ISSN | Citations |
13 | 0016-0032 | 0 |
PageRank | References | Authors |
0.34 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jie Gao | 1 | 2174 | 155.61 |
| Peiyong Zhu | 2 | 59 | 8.68 |
| Wenjun Xiong | 3 | 225 | 20.20 |
| Jinde Cao | 4 | 11399 | 733.03 |
| Lin Zhang | 5 | 104 | 51.47 |