Paper Info
Title
Exponential stability and extended dissipativity criteria for generalized neural networks with interval time-varying delay signals.
Abstract
This paper discusses the problems of exponential stability and extended dissipativity analysis of generalized neural networks (GNNs) with time delays. A new criterion for the exponential stability and extended dissipativity of GNNs is established based on the suitable Lyapunov–Krasovskii functionals (LKFs) together with the Wirtinger single integral inequality (WSII) and Wirtinger double integral inequality (WDII) technique, and that is mixed with the reciprocally convex combination (RCC) technique. An improved exponential stability and extended dissipativity criterion for GNNs are expressed in terms of linear matrix inequalities (LMIs). The major contributions of this study are an exponential stability and extended dissipativity concept can be developed to analyze simultaneously the solutions of the exponential H∞, L2−L∞, passivity, and dissipativity performance for GNNs by selecting the weighting matrices. Finally, several interesting numerical examples are developed to verify the usefulness of the proposed results, among them one example was supported by real-life application of the benchmark problem that associates with reasonable issues under extended dissipativity performance.
Year
DOI
Venue
2017
10.1016/j.jfranklin.2017.04.007
Journal of the Franklin Institute
Field
DocType
Volume
Passivity,Mathematical optimization,Weighting,Exponential function,Matrix (mathematics),Control theory,Convex combination,Exponential stability,Multiple integral,Artificial neural network,Mathematics
Journal
354
Issue
ISSN
Citations 
11
0016-0032
18
PageRank 
References 
Authors
0.59
29
5
Name
Order
Citations
PageRank
Raman Manivannan11546.59
G. Mahendrakumar2180.59
R. Samidurai327515.47
Jinde Cao411399733.03
A. Alsaedi574963.55