TY - JOUR
T1 - New stability criteria for recurrent neural networks with a time-varying delay
AU - Zeng, Hong Bing
AU - Xiao, Shen Ping
AU - Liu, Bin
PY - 2011/2
Y1 - 2011/2
N2 - This paper deals with the stability of static recurrent neural networks (RNNs) with a time-varying delay. An augmented Lyapunov-Krasovskii functional is employed, in which some useful terms are included. Furthermore, the relationship among the time-varying delay, its upper bound and their difference, is taken into account, and novel bounding techniques for 1 - τ(t) are employed. As a result, without ignoring any useful term in the derivative of the Lyapunov-Krasovskii functional, the resulting delay-dependent criteria show less conservative than the existing ones. Finally, a numerical example is given to demonstrate the effectiveness of the proposed methods.
AB - This paper deals with the stability of static recurrent neural networks (RNNs) with a time-varying delay. An augmented Lyapunov-Krasovskii functional is employed, in which some useful terms are included. Furthermore, the relationship among the time-varying delay, its upper bound and their difference, is taken into account, and novel bounding techniques for 1 - τ(t) are employed. As a result, without ignoring any useful term in the derivative of the Lyapunov-Krasovskii functional, the resulting delay-dependent criteria show less conservative than the existing ones. Finally, a numerical example is given to demonstrate the effectiveness of the proposed methods.
KW - Stability
KW - augmented Lyapunov-Krasovskii functional
KW - delay-dependent
KW - recurrent neural networks (RNNs)
KW - time-varying delay
UR - http://www.scopus.com/inward/record.url?scp=79952320284&partnerID=8YFLogxK
U2 - 10.1007/s11633-010-0564-y
DO - 10.1007/s11633-010-0564-y
M3 - Article
SN - 1476-8186
VL - 8
SP - 128
EP - 133
JO - International Journal of Automation and Computing
JF - International Journal of Automation and Computing
IS - 1
ER -