Title
Novel global robust exponential stability criterion for uncertain inertial-type BAM neural networks with discrete and distributed time-varying delays via Lagrange sense.
Abstract
In this paper, the global robust exponential stability problem for a class of uncertain inertial-type BAM neural networks with both time-varying delays is focused through Lagrange sense. The existence of time-varying delays in discrete and distributed terms is explored with the availability of lower and upper bounds of time-varying delays. Firstly, we transform the proposed inertial BAM neural networks to usual one. Secondly, by the aid of LKF, stability theory, integral inequality, some novel sufficient conditions for the global robust exponential stability of the addressed neural networks are obtained in terms of linear matrix inequalities, which can be easily tested in practice by utilizing LMI control toolbox in MATLAB software. Furthermore, many comparisons of proposed work are listed with some existing literatures to get less conservatism. Finally, two numerical examples are provided to demonstrate the advantages and superiority of our theoretical outcomes.
Year
DOI
Venue
2018
10.1016/j.jfranklin.2018.04.034
Journal of the Franklin Institute
Field
DocType
Volume
Inertial frame of reference,MATLAB,Control theory,Matrix (mathematics),Toolbox,Software,Exponential stability,Artificial neural network,Mathematics,Stability theory
Journal
355
Issue
ISSN
Citations 
11
0016-0032
5
PageRank 
References 
Authors
0.40
33
4
Name
Order
Citations
PageRank
C. Maharajan1171.56
R. Raja218012.58
Jinde Cao311399733.03
Grienggrai Rajchakit410011.87