Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6865275 | Neurocomputing | 2018 | 24 Pages |
Abstract
This paper is concerned with the global asymptotic stability and global robust stability of inertial neural networks with proportional delays. First, by using linear matrix inequality and constructing appropriate Lyapunov functional, several sufficient conditions are obtained for the global asymptotic stability of inertial neural networks with proportional delays. Furthermore, the problem of global robust stability of the network under the assumptions that the network parameters are uncertain and bounded is studied. Finally, some simulation examples are presented to demonstrate the effectiveness of the proposed method.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Na Cui, Haijun Jiang, Cheng Hu, Abdujelil Abdurahman,