Title
Non-fragile extended dissipative synchronization of Markov jump inertial neural networks: An event-triggered control strategy
Abstract
In this paper, the non-fragile extended dissipative synchronization issue is studied for Markov jump neural networks with inertial term. With regard to the inertial neural networks described by a second-order differential equation, an appropriate variable substitution is applied to transform the original system into a first-order differential system. Considering that the data transmissions are proceed in the shared band-limited digital communication networks when designing a controller to achieve synchronization. In order to alleviate the burden of networked communication, a controller based on an event-triggered strategy is used to achieve this goal. Furthermore, a non-fragile controller design scheme governed by Bernoulli distribution is proposed to deal with the uncertainty that may occur in the implementation process of the designed controller. Then, on the basis of the Lyapunov stability theory and an improved inequality technique, sufficient conditions are obtained to ensure that the error system meets the extended dissipative synchronization. Finally, two examples are provided to verify the effectiveness of the proposed results.
Year
DOI
Venue
2021
10.1016/j.neucom.2021.07.016
Neurocomputing
Keywords
DocType
Volume
Markov jump inertial neural networks,Event-triggered strategy,Non-fragile controller,Extended dissipative,Synchronization
Journal
460
ISSN
Citations 
PageRank 
0925-2312
0
0.34
References 
Authors
0
4
Name
Order
Citations
PageRank
Tian Fang100.34
Shiyu Jiao221.05
Fu Dongmei343.08
Jing Wang450793.00