Further improved results on stability and dissipativity analysis of static impulsive neural networks with interval time-varying delays

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)-gamma-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 gamma-dependent condition is given to guarantee that the SNNs with interval time-varying delays are strictly (Q, S, R)-gamma-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. (C) 2017 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.