On stability analysis for neural networks with interval time-varying delays via some new augmented Lyapunov-Krasovskii functional

Title
On stability analysis for neural networks with interval time-varying delays via some new augmented Lyapunov-Krasovskii functional
Author(s)
박주현O.M. Kwon[O.M. Kwon]M.J. Park[M.J. Park]S.M. Lee[S.M. Lee]E.J. Cha[E.J. Cha]
Keywords
MARKOVIAN JUMPING PARAMETERS; DEPENDENT STABILITY; ROBUST STABILITY; EXPONENTIAL STABILITY; DISTRIBUTED DELAY; STATE ESTIMATION; NEUTRAL-TYPE; CRITERIA; SYSTEMS; STABILIZATION
Issue Date
201409
Publisher
ELSEVIER SCIENCE BV
Citation
COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION, v.19, no.9, pp.3184 - 3201
Abstract
This paper is concerned with the problem of stability analysis of neural networks with interval time-varying delays. It is assumed that the lower bound of time-varying delays is not restricted to be zero. By constructing a newly augmented Lyapunov-Krasovskii functional which has not been proposed yet and utilizing some integral information on activation function as elements of augmented vectors, an improved stability criterion with the framework of linear matrix inequalities (LMIs) is introduced in Theorem 1. Based on the result of Theorem 1 and utilizing the property of the positiveness of Lyapunov-Krasovskii functional, a further relaxed stability condition will be proposed in Theorem 2. The effectiveness and less conservatism of the proposed theorems will be illustrated via three numerical examples. (C) 2014 Elsevier B. V. All rights reserved.
URI
http://hdl.handle.net/YU.REPOSITORY/30904http://dx.doi.org/10.1016/j.cnsns.2014.02.024
ISSN
1007-5704
Appears in Collections:
공과대학 > 전기공학과 > Articles
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