Name
Title | ||
|---|---|---|
Existence and global exponential stability of periodic solutions of recurrent cellular neural networks with impulses and delays |
Abstract | ||
|---|---|---|
By using the continuation theorem of coincidence degree theory and constructing suitable Lyapunov functions, we study the existence, uniqueness and global exponential stability of periodic solutions for recurrent neural networks with impulsive perturbations and delays. Further, by using numerical simulation method, the influences of the impulsive perturbations on the inherent oscillations are investigated. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1016/j.matcom.2007.09.001 | Mathematics and Computers in Simulation |
Keywords | DocType | Volume |
recurrent cellular neural network,coincidence degree theory,quasi-periodic solution,neural networks,continuation theorem,impulsive effect,periodic solution,suitable lyapunov function,simulation method,global exponential stability,impulsive perturbation,inherent oscillation,recurrent neural network,numerical simulation method,neural network,lyapunov function,cellular neural network,oscillations,numerical simulation | Journal | 79 |
Issue | ISSN | Citations |
1 | Mathematics and Computers in Simulation | 10 |
PageRank | References | Authors |
1.23 | 6 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhanji Gui | 1 | 35 | 5.94 |
| Xiaosong Yang | 2 | 378 | 52.10 |
| Weigao Ge | 3 | 158 | 46.20 |