Abstract
The problem of stability of dynamical neural networks with uncertain delays is studied, where uncertain delays are assumed to be constant. In this paper, a new approach is developed to establish delay-dependent sufficient conditions for asymptotic stability of delayed neural networks. The new approach is a combination of the discretized Lyapunov functional method and the free-weighting matrix technique. The established delay- dependent sufficient conditions are expressed by means of linear matrix inequalities, and thus are easily checkable. The new delay-dependent stability conditions are further illustrated by numerical results and are also compared with the existing results.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 47th IEEE Conference on Decision and Control, held in Cancun, Mexico, 9-11 December, 2009 |
| Publisher | IEEE |
| Number of pages | 6 |
| ISBN (Print) | 9781424431243 |
| Publication status | Published - 2009 |
| Event | IEEE Conference on Decision and Control - Duration: 12 Dec 2017 → … |
Conference
| Conference | IEEE Conference on Decision and Control |
|---|---|
| Period | 12/12/17 → … |
Keywords
- Lyapunov functions
- neural networks (computer science)
- stability
- delays