Improved Conditions for Passivity of Neural Networks With a Time-Varying Delay

Author

Hong-Bing Zeng ; Yong He ; Min Wu ; Hui-Qin Xiao

Author_Institution

Sch. of Inf. Sci. & Eng., Central South Univ., Changsha, China

Volume

44

Issue

6

fYear

2014

fDate

Jun-14

Firstpage

785

Lastpage

792

Abstract

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.

Keywords

Lyapunov methods; delays; matrix algebra; neural nets; Lyapunov-Krasovskii functional; delay-decomposing approach; free-weighting matrices; improved passivity criteria; neural networks; norm-bounded parameter uncertainties; segmentation technique; time-varying delay; Biological neural networks; Delay effects; Delays; Educational institutions; Stability analysis; Symmetric matrices; Lyapunov-Krasovskii functional; Lyapunov??Krasovskii functional; neural networks; passivity; time-varying delay;

fLanguage

English

Journal_Title

Cybernetics, IEEE Transactions on

Publisher

ieee

ISSN

2168-2267

Type

jour

DOI

10.1109/TCYB.2013.2272399

Filename

6728636