Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
407106 | Neural Networks | 2010 | 6 Pages |
Abstract
This paper is concerned with the state estimation problem for a class of static neural networks with time-varying delay. Here the time derivative of the time-varying delay is no longer required to be smaller than one. A delay partition approach is proposed to derive a delay-dependent condition under which the resulting error system is globally asymptotically stable. The design of a desired state estimator for such kinds of delayed neural networks can be accomplished by means of solving a linear matrix inequality. A simulation example is finally given to show the application of the developed approach.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
He Huang, Gang Feng, Jinde Cao,