Paper Info
Title
Further improved results on stability and dissipativity analysis of static impulsive neural networks with interval time-varying delays.
Abstract
This paper deals with the problem of stability and dissipativity analysis for a class of static neural networks (SNNs) with interval time-varying delays. The system under study involves impulsive effects and time delays, which are often encountered in practice and are the sources of instability. Our attention is focused on the an analysis of whether the system is asymptotically stable and strictly (Q,S,R)−γ- dissipative. Based on the Wirtinger-based single and double integral inequality technique combined with the free-weighting-matrix approach which is expressed in terms of linear matrix inequalities (LMIs), we propose an improved delay-dependent stability and dissipativity criterion to guarantee the system to be admissible. Based on this criterion, a new sufficient delay and γ-dependent condition is given to guarantee that the SNNs with interval time-varying delays are strictly (Q,S,R)−γ- dissipative. Finally, the results developed in this paper can tolerate larger allowable delay bounds than the existing ones in the recent literature, which is demonstrated by several interesting examples.
Year
DOI
Venue
2017
10.1016/j.jfranklin.2017.07.040
Journal of the Franklin Institute
Field
DocType
Volume
Mathematical optimization,Matrix (mathematics),Control theory,Dissipative system,Instability,Multiple integral,Artificial neural network,Mathematics,Stability theory
Journal
354
Issue
ISSN
Citations 
14
0016-0032
16
PageRank 
References 
Authors
0.54
36
3
Name
Order
Citations
PageRank
Raman Manivannan11546.59
R. Samidurai227515.47
Quanxin Zhu3110067.69