Title
Dissipativity of discrete-time BAM stochastic neural networks with Markovian switching and impulses
Abstract
This paper addresses the problem of global exponential dissipativity for a class of uncertain discrete-time BAM stochastic neural networks with time-varying delays, Markovian jumping and impulses. By constructing a proper Lyapunov–Krasovskii functional and combining with linear matrix inequality (LMI) technique, several sufficient conditions are derived for verifying the global exponential dissipativity in the mean square of such stochastic discrete-time BAM neural networks. The derived conditions are established in terms of linear matrix inequalities, which can be easily solved by some available software packages. One important feature presented in our paper is that without employing model transformation and free-weighting matrices our obtained result leads to less conservatism. Additionally, three numerical examples with simulation results are provided to show the effectiveness and usefulness of the obtained result.
Year
DOI
Venue
2013
10.1016/j.jfranklin.2013.08.003
Journal of the Franklin Institute
Field
DocType
Volume
Mathematical optimization,Model transformation,Exponential function,Matrix (mathematics),Control theory,Stochastic neural network,Software,Discrete time and continuous time,Artificial neural network,Mathematics,Linear matrix inequality
Journal
350
Issue
ISSN
Citations 
10
0016-0032
21
PageRank 
References 
Authors
0.67
26
4
Name
Order
Citations
PageRank
R. Raja118012.58
U. Karthik Raja2422.01
R. Samidurai3362.25
A. Leelamani4483.75