TY - JOUR
T1 - A new global robust stability criteria for uncertain neural networks with fast time-varying delays
AU - Qiu, Jiqing
AU - Zhang, Jinhui
AU - Wang, Jianfei
AU - Xia, Yuanqing
AU - Shi, Peng
PY - 2008/7
Y1 - 2008/7
N2 - This paper deals with the problem of robust stability for uncertain neural networks with time-varying delays. The system possesses time-varying and norm-bounded uncertainties. The time-varying delay function in this paper is not required to be either continuously differentiable, or its derivative less than one. Based on Lyapunov-Krasovskii functional approach, new delay-dependent and delay-derivative-dependent stability criteria are presented, which are given in terms of linear matrix inequalities (LMIs). Numerical examples are given to illustrate the effectiveness and less conservativeness of the developed techniques.
AB - This paper deals with the problem of robust stability for uncertain neural networks with time-varying delays. The system possesses time-varying and norm-bounded uncertainties. The time-varying delay function in this paper is not required to be either continuously differentiable, or its derivative less than one. Based on Lyapunov-Krasovskii functional approach, new delay-dependent and delay-derivative-dependent stability criteria are presented, which are given in terms of linear matrix inequalities (LMIs). Numerical examples are given to illustrate the effectiveness and less conservativeness of the developed techniques.
UR - http://www.scopus.com/inward/record.url?scp=40749147693&partnerID=8YFLogxK
U2 - 10.1016/j.chaos.2007.10.040
DO - 10.1016/j.chaos.2007.10.040
M3 - Article
AN - SCOPUS:40749147693
SN - 0960-0779
VL - 37
SP - 360
EP - 368
JO - Chaos, Solitons and Fractals
JF - Chaos, Solitons and Fractals
IS - 2
ER -