Master–slave exponential synchronization of delayed complex-valued memristor-based neural networks via impulsive control

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 trans...

Full description

Saved in:
Bibliographic Details
Published in:Neural networks 2017-09, Vol.93, p.165-175
Main Authors: Li, Xiaofan, Fang, Jian-an, Li, Huiyuan
Format: Article
Language:English
Subjects:
Complex-value memristor-based neural networks
Exponential synchronization
Impulsive control
Neural Networks (Computer)
Nonlinear Dynamics
Time-varying delays
Transistors, Electronic
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
ISSN:0893-6080
1879-2782
DOI:10.1016/j.neunet.2017.05.008