Name
Title | ||
|---|---|---|
Global Robust Exponential Stability for Interval Delayed Neural Networks with Possibly Unbounded Activation Functions |
Abstract | ||
|---|---|---|
In this paper, we mainly study the global robust exponential stability of the neural networks with possibly unbounded activation functions. Based on the topological degree theory and Lyapunov functional method, we provide some new sufficient conditions for the global robust exponential stability. Under these conditions, we prove existence, uniqueness and global robust exponential stability of equilibrium point. In the end, some examples are provided to demonstrate the validity of the theoretical results. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1007/s11063-013-9309-6 | Neural Processing Letters |
Keywords | Field | DocType |
Delayed neural networks with possibly unbounded activation,Global robust exponential stability,Topological degree theory | Uniqueness,Applied mathematics,Pattern recognition,Mathematical analysis,Equilibrium point,Exponential stability,Artificial intelligence,Topological degree theory,Artificial neural network,Lyapunov functional,Mathematics | Journal |
Volume | Issue | ISSN |
40 | 1 | 1370-4621 |
Citations | PageRank | References |
3 | 0.38 | 24 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sitian Qin | 1 | 244 | 23.00 |
| Dejun Fan | 2 | 3 | 0.38 |
| Ming Yan | 3 | 99 | 8.39 |
| Qinghe Liu | 4 | 3 | 0.38 |