Title
Unified synchronization criteria in an array of coupled neural networks with hybrid impulses.
Abstract
This paper investigates the problem of globally exponential synchronization of coupled neural networks with hybrid impulses. Two new concepts on average impulsive interval and average impulsive gain are proposed to deal with the difficulties coming from hybrid impulses. By employing the Lyapunov method combined with some mathematical analysis, some efficient unified criteria are obtained to guarantee the globally exponential synchronization of impulsive networks. Our method and criteria are proved to be effective for impulsively coupled neural networks simultaneously with synchronizing impulses and desynchronizing impulses, and we do not need to discuss these two kinds of impulses separately. Moreover, by using our average impulsive interval method, we can obtain an interesting and valuable result for the case of average impulsive interval Ta=∞. For some sparse impulsive sequences with Ta=∞, the impulses can happen for infinite number of times, but they do not have essential influence on the synchronization property of networks. Finally, numerical examples including scale-free networks are exploited to illustrate our theoretical results.
Year
DOI
Venue
2018
10.1016/j.neunet.2018.01.017
Neural Networks
Keywords
Field
DocType
Coupled neural networks,Synchronization,Average impulsive interval,Average impulsive gain,Hybrid impulses
Interval method,Lyapunov function,Synchronization,Mathematical optimization,Control theory,Synchronizing,Exponential synchronization,Artificial neural network,Mathematics
Journal
Volume
Issue
ISSN
101
1
0893-6080
Citations 
PageRank 
References 
4
0.41
28
Authors
4
Name
Order
Citations
PageRank
Nan Wang19327.47
Xuechen Li2326.98
Jianquan Lu32337116.05
Fuad E. Alsaadi41818102.89