Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4946728 | Neural Networks | 2016 | 13 Pages |
Abstract
In this paper, stability for a class of uncertain switched neural networks with time-varying delay is investigated. By exploring the mode-dependent properties of each subsystem, all the subsystems are categorized into stable and unstable ones. Based on Lyapunov-like function method and average dwell time technique, some delay-dependent sufficient conditions are derived to guarantee the exponential stability of considered uncertain switched neural networks. Compared with general results, our proposed approach distinguishes the stable and unstable subsystems rather than viewing all subsystems as being stable, thus getting less conservative criteria. Finally, two numerical examples are provided to show the validity and the advantages of the obtained results.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Wenwen Shen, Zhigang Zeng, Leimin Wang,