Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
494482 | Neurocomputing | 2016 | 11 Pages |
Abstract
In this paper, a class of delayed complex-valued neural networks with impulses is investigated. By using Mawhin׳s continuation theorem of coincidence degree theory, a series of useful criteria on existence of periodic solution are established for the complex-valued neural networks. By constructing appropriate Lyapunov–Krasovskii functional, some sufficient conditions are derived for the global exponential stability of periodic solutions to the complex-valued neural networks. Finally, several examples with numerical simulations are given to highlight the effectiveness of our theoretical results via standard numerical software.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Dong Xie, Yueping Jiang,