TY - JOUR
T1 - Delay-dependent stability criteria for reaction-diffusion neural networks with time-varying delays
AU - Ma, Qian
AU - Feng, Gang
AU - Xu, Shengyuan
PY - 2013/12
Y1 - 2013/12
N2 - This paper studies the global asymptotic stability problem of a class of reaction-diffusion neural networks with time-varying delays. To overcome the difficulty caused by the partial differential term, a novel Lyapunov-Krasovskii functional is proposed, and a partial differential equation technique together with a linear operator approach are also applied to obtain the delay-dependent stability criteria, which are less conservative than the existing results. Finally, simulation examples are given to verify and illustrate the theoretical analysis. © 2013 IEEE.
AB - This paper studies the global asymptotic stability problem of a class of reaction-diffusion neural networks with time-varying delays. To overcome the difficulty caused by the partial differential term, a novel Lyapunov-Krasovskii functional is proposed, and a partial differential equation technique together with a linear operator approach are also applied to obtain the delay-dependent stability criteria, which are less conservative than the existing results. Finally, simulation examples are given to verify and illustrate the theoretical analysis. © 2013 IEEE.
KW - Asymptotic stability
KW - Delay-dependent stability criteria
KW - Lyapunov-Krasovskii functional
KW - Reaction-diffusion neural networks
UR - http://www.scopus.com/inward/record.url?scp=84890097051&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-84890097051&origin=recordpage
U2 - 10.1109/TSMCB.2012.2235178
DO - 10.1109/TSMCB.2012.2235178
M3 - RGC 21 - Publication in refereed journal
C2 - 23757581
SN - 2168-2267
VL - 43
SP - 1913
EP - 1920
JO - IEEE Transactions on Cybernetics
JF - IEEE Transactions on Cybernetics
IS - 6
M1 - 6449305
ER -