TY - JOUR
T1 - Stability analysis of static recurrent neural networks with interval time-varying delay
AU - Sun, Jian
AU - Chen, Jie
PY - 2013
Y1 - 2013
N2 - The problem of stability analysis of static recurrent neural networks with interval time-varying delay is investigated in this paper. A new Lyapunov functional which contains some new double integral and triple integral terms are introduced. Information about the lower bound of the delay is fully used in the Lyapunov functional. Integral and double integral terms in the derivative of the Lyapunov functional are divided into some parts to get less conservative results. Some sufficient stability conditions are obtained in terms of linear matrix inequality (LMI). Numerical examples are given to illustrate the effectiveness of the proposed method.
AB - The problem of stability analysis of static recurrent neural networks with interval time-varying delay is investigated in this paper. A new Lyapunov functional which contains some new double integral and triple integral terms are introduced. Information about the lower bound of the delay is fully used in the Lyapunov functional. Integral and double integral terms in the derivative of the Lyapunov functional are divided into some parts to get less conservative results. Some sufficient stability conditions are obtained in terms of linear matrix inequality (LMI). Numerical examples are given to illustrate the effectiveness of the proposed method.
KW - Delay-dependent stability
KW - Interval time-varying delay
KW - Linear matrix inequality
KW - Static recurrent neural network
UR - http://www.scopus.com/inward/record.url?scp=84880337003&partnerID=8YFLogxK
U2 - 10.1016/j.amc.2013.06.028
DO - 10.1016/j.amc.2013.06.028
M3 - Article
AN - SCOPUS:84880337003
SN - 0096-3003
VL - 221
SP - 111
EP - 120
JO - Applied Mathematics and Computation
JF - Applied Mathematics and Computation
ER -