A new approach to stability analysis of neural networks with time-varying delay via novel Lyapunov-Krasovskii functional

Title
A new approach to stability analysis of neural networks with time-varying delay via novel Lyapunov-Krasovskii functional
Author(s)
박주현S.M. Lee[S.M. Lee]O.M. Kwon[O.M. Kwon]
Keywords
ABSOLUTE STABILITY; ROBUST STABILITY; GLOBAL STABILITY; LURE SYSTEMS; CRITERIA; SYNCHRONIZATION; NONLINEARITIES; DISCRETE; SECTOR
Issue Date
201005
Publisher
IOP PUBLISHING LTD
Citation
CHINESE PHYSICS B, v.19, no.5
Abstract
In this paper, new delay-dependent stability criteria for asymptotic stability of neural networks with time-varying delays are derived. The stability conditions are represented in terms of linear matrix inequalities (LMIs) by constructing new Lyapunov-Krasovskii functional. The proposed functional has an augmented quadratic form with states as well as the nonlinear function to consider the sector and the slope constraints. The less conservativeness of the proposed stability criteria can be guaranteed by using convex properties of the nonlinear function which satisfies the sector and slope bound. Numerical examples are presented to show the effectiveness of the proposed method.
URI
http://hdl.handle.net/YU.REPOSITORY/22460http://dx.doi.org/10.1088/1674-1056/19/5/050507
ISSN
1674-1056
Appears in Collections:
공과대학 > 전기공학과 > Articles
Files in This Item:
There are no files associated with this item.
Export
RIS (EndNote)
XLS (Excel)
XML


qrcode

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

BROWSE