Further improved results on stability and dissipativity analysis of static impulsive neural networks with interval time-varying delays. Issue 14 (September 2017)

• Record Type: Journal Article
• Authors: Manivannan, R.; Samidurai, R.; Zhu, Quanxin
• Is Part Of: Journal of the Franklin Institute. Volume 354:Issue 14(2017)
• Page Start: 6312
• Page End: 6340
• Publication Date: 2017-09
• Subjects: Science -- Periodicals; Technology -- Periodicals; Patents -- United States -- Periodicals; 505
• DOI: 10.1016/j.jfranklin.2017.07.040
• Languages: English
• ISSNs: 0016-0032

Abstract

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.