TY - JOUR
T1 - Global robust stability for delayed neural networks with polytopic type uncertainties
AU - He, Yong
AU - Wang, Qing-Guo
AU - Zheng, Wei Xing
PY - 2005
Y1 - 2005
N2 - In this paper, global robust stability for delayed neural networks is studied. First the free-weighting matrices are employed to express the relationship between the terms in the system equation, and a stability condition for delayed neural networks is derived by using the S-procedure. Then this result is extended to establish a global robust stability criterion for delayed neural networks with polytopic type uncertainties. A numerical example given in [IEEE Trans Circuits Syst II 52 (2005) 33–36] for interval delayed neural networks is investigated. The effectiveness of the presented global robust stability criterion and its improvement over the existing results are demonstrated.
AB - In this paper, global robust stability for delayed neural networks is studied. First the free-weighting matrices are employed to express the relationship between the terms in the system equation, and a stability condition for delayed neural networks is derived by using the S-procedure. Then this result is extended to establish a global robust stability criterion for delayed neural networks with polytopic type uncertainties. A numerical example given in [IEEE Trans Circuits Syst II 52 (2005) 33–36] for interval delayed neural networks is investigated. The effectiveness of the presented global robust stability criterion and its improvement over the existing results are demonstrated.
KW - global robust stability
KW - matrices
KW - neural networks, foundations to applications
UR - http://handle.uws.edu.au:8081/1959.7/34407
M3 - Article
SN - 0960-0779
JO - Chaos\, Solitons & Fractals
JF - Chaos\, Solitons & Fractals
ER -