| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 710166 | IFAC-PapersOnLine | 2016 | 6 Pages |
Abstract
This note investigates the problem of exponential stability of neural networks with time-varying delays. To derive a less conservative stability condition, a novel augmented Lyapunov-Krasovskii functional (LKF) which includes triple and quadruple-integral terms is employed. In order to reduce the complexity of the stability test, the convex combination method is utilized to derive an improved delay-dependent stability criterion in the form of linear matrix inequalities (LMIs). The superiority of the proposed approach is demonstrated by two comparative examples.
Related Topics
Physical Sciences and Engineering
Engineering
Computational Mechanics
Authors
Arash Farnam, Reza Mahboobi Esfanjani, Aghil Ahmadi,