Name
Title | ||
|---|---|---|
Globally Exponential Stability of Neural Networks with Impulses and Distributed Delays |
Abstract | ||
|---|---|---|
In this paper, the main purpose is to study the global exponential stability of the equilibrium point for a class of cellular neural networks with impulses and distributed delays. With the assumption of global Lipschitz conditions on the activation function, applying idea of vector Lyapunov function, combining Halanay differential inequality with delay, a sufficient condition for globally exponential stability of neural networks is obtained. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/WGEC.2009.33 | WGEC |
Keywords | Field | DocType |
halanay differential inequality,neural network,neural networks,global lipschitz conditions,asymptotic stability,transfer functions,global exponential stability,lyapunov function,neural network globally exponential stability,delays,cellular neural network,main purpose,exponential stability,neural network impulses,activation function,equilibrium point,globally exponential stability,neural network distributed delays,global lipschitz condition,vector lyapunov function,lyapunov methods,neural nets,stability analysis,artificial neural networks,lipschitz condition,cellular neural networks | Lyapunov function,Mathematical optimization,Computer science,Control theory,Activation function,Equilibrium point,Exponential stability,Transfer function,Lipschitz continuity,Artificial neural network,Cellular neural network | Conference |
ISBN | Citations | PageRank |
978-0-7695-3899-0 | 0 | 0.34 |
References | Authors | |
5 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jianfu Yang | 1 | 3 | 2.87 |
| Ren Liu | 2 | 28 | 6.14 |
| Fengjian Yang | 3 | 33 | 5.60 |
| Wei Li | 4 | 0 | 1.35 |
| Dongqing Wu | 5 | 31 | 5.50 |