Title
Synchronization of impulsive coupled complex-valued neural networks with delay: The matrix measure method.
Abstract
In this paper, the exponential synchronization of the impulsive coupled delayed complex-valued neural networks (CVNNs) is studied. Without constructing the Lyapunov function, a novel approach based on the matrix measure and extended Halanay inequality is presented and some sufficient criteria for exponential synchronization of the addressed CVNNs are derived. In this paper, the restriction of the real and imaginary parts of activation functions which are supposed to depend only on the real and imaginary parts of the variables, respectively, is removed. Furthermore, by employing the average impulsive interval method, the requirement on the upper bound of the impulsive intervals is removed for impulsive signal transmission. Finally, numerical examples are provided to demonstrate the effectiveness of the theoretical results obtained, even for large-scale CVNNs with impulsive coupling.
Year
DOI
Venue
2019
10.1016/j.neunet.2019.05.024
Neural Networks
Keywords
Field
DocType
Complex-valued neural networks,Synchronization,Matrix measure,Impulsive control
Interval method,Lyapunov function,Applied mathematics,Transmission (telecommunications),Mathematical optimization,Synchronization,Coupling,Matrix (mathematics),Upper and lower bounds,Artificial neural network,Mathematics
Journal
Volume
Issue
ISSN
117
1
0893-6080
Citations 
PageRank 
References 
5
0.40
0
Authors
3
Name
Order
Citations
PageRank
Lulu Li135718.42
Xiaohong Shi250.40
Jinling Liang31985105.88