Title
Mean square synchronization of neural networks with Lévy noise via sampled-data and actuator saturating controller.
Abstract
The problem of synchronization via sampled-data and saturating controller is considered for stochastic time-delay neural networks with Lévy noise and Markovian switching parameters in this paper. By using of the generalized Itô׳s formula and the Lyapunov functional method, an LMI-based sufficient condition is established to ensure the mean square synchronization of the master system and the slave system. Meanwhile, the gain of the sample data and saturating controller is determined. The sufficient condition depends on not only the switching mode and time-delay, but also the upper and the lower bound of sampling intervals. A numerical example is provided to verify the usefulness of the criterion proposed in this paper.
Year
DOI
Venue
2016
10.1016/j.neucom.2015.08.081
Neurocomputing
Keywords
Field
DocType
Neural networks,Lévy noise,Markovian switching parameters,Sampled-data and actuator saturating controller,Synchronization
Mean square,Control theory,Synchronization,Control theory,Upper and lower bounds,Sampling (statistics),Artificial neural network,Lyapunov functional,Mathematics,Actuator
Journal
Volume
ISSN
Citations 
173
0925-2312
7
PageRank 
References 
Authors
0.44
18
4
Name
Order
Citations
PageRank
Liuwei Zhou1592.79
Zhijie Wang28911.14
Jun Zhou3293.21
Wuneng Zhou446753.74