Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
412924 | Neurocomputing | 2010 | 5 Pages |
Abstract
This paper is concerned with the stability for static neural networks with time-varying delays. With an appropriate Lyapunov functional formulated, a new technique is proposed to up bound the derivative of the Lyapunov functional. A delay-dependent stability criterion is obtained by proving the bound negative definite with convex combination methods. The delay-dependent stability criterion is simpler and less conservative than some existing ones. Both delay-independent and delay-dependent criteria are obtained, which can be checked easily using the recently developed algorithms. Examples are provided to illustrate the effectiveness and the reduced conservatism of the proposed results.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Hanyong Shao,