| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 10151209 | Neurocomputing | 2018 | 9 Pages |
Abstract
This brief presents a class of delayed second-order memristive neural networks (SMNNs). By building a new Lyapunov functional and employing some inequalities technique, we derive some new criteria ensuring global exponential stability of the delayed SMNNs. Compared with other researches on dynamics of neural networks (NNs), our system is described by second-order differential equations and memristor. In addition, we discuss the SMNNs directly and the main results given here without changing the SMNNs into the first-order differential systems. Finally, simulations are given to elaborate the validity of the obtained criteria.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Guodong Zhang, Junhao Hu, Feng Jiang,