TY - JOUR
T1 - A new LMI condition for delay-dependent asymptotic stability of delayed Hopfield neural networks
AU - Xu, Shengyuan
AU - Lam, James
AU - Ho, Daniel W.C.
PY - 2006/3
Y1 - 2006/3
N2 - In this paper, a new delay-dependent asymptotic stability condition for delayed Hopfield neural networks is given in terms of a linear matrix inequality, which is less conservative than existing ones in the literature. This condition guarantees the existence of a unique equilibrium point and its global asymptotic stability of a given delayed Hopfield neural network. Examples are provided to show the reduced conservatism of the proposed condition. © 2006 IEEE.
AB - In this paper, a new delay-dependent asymptotic stability condition for delayed Hopfield neural networks is given in terms of a linear matrix inequality, which is less conservative than existing ones in the literature. This condition guarantees the existence of a unique equilibrium point and its global asymptotic stability of a given delayed Hopfield neural network. Examples are provided to show the reduced conservatism of the proposed condition. © 2006 IEEE.
KW - Global asymptotic stability
KW - Hopfield neural networks
KW - Linear matrix inequality
KW - Time delays
UR - http://www.scopus.com/inward/record.url?scp=33644993005&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-33644993005&origin=recordpage
U2 - 10.1109/TCSII.2005.857764
DO - 10.1109/TCSII.2005.857764
M3 - RGC 21 - Publication in refereed journal
SN - 1549-7747
VL - 53
SP - 230
EP - 234
JO - IEEE Transactions on Circuits and Systems II: Express Briefs
JF - IEEE Transactions on Circuits and Systems II: Express Briefs
IS - 3
ER -