Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4946620 | Neural Networks | 2017 | 20 Pages |
Abstract
This paper investigates master-slave exponential synchronization for a class of complex-valued memristor-based neural networks with time-varying delays via discontinuous impulsive control. Firstly, the master and slave complex-valued memristor-based neural networks with time-varying delays are translated to two real-valued memristor-based neural networks. Secondly, an impulsive control law is constructed and utilized to guarantee master-slave exponential synchronization of the neural networks. Thirdly, the master-slave synchronization problems are transformed into the stability problems of the master-slave error system. By employing linear matrix inequality (LMI) technique and constructing an appropriate Lyapunov-Krasovskii functional, some sufficient synchronization criteria are derived. Finally, a numerical simulation is provided to illustrate the effectiveness of the obtained theoretical results.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Xiaofan Li, Jian-an Fang, Huiyuan Li,