Improved conditions for passivity of neural networks with a time-varying delay.
The passivity of neural networks with a time-varying delay and norm-bounded parameter uncertainties is investigated in this paper. A complete delay-decomposing approach is employed to construct a Lyapunov-Krasovskii functional. Then, by utilizing a segmentation technique to consider the time-varying delay and its derivative and introducing some free-weighting matrices to express the relationship between the time-varying delay and its varying interval, some improved passivity criteria are derived. Finally, two numerical examples are given to show the effectiveness and the merits of the proposed method.
Hong-Bing
HB
Zeng
Yong
Y
He
Min
M
Wu
Hui-Qin
HQ
Xiao
D000465:Algorithms; D003198:Computer Simulation; D016571:Neural Networks, Computer; D013997:Time Factors