New criteria on delay-dependent stability for discrete-time neural networks with time-varying delays

Title
New criteria on delay-dependent stability for discrete-time neural networks with time-varying delays
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
EXPONENTIAL STABILITY; ROBUST STABILITY; LINEAR-SYSTEMS; STABILIZATION; UNCERTAINTIES; DYNAMICS; ARRAYS
Issue Date
201312
Publisher
ELSEVIER SCIENCE BV
Citation
NEUROCOMPUTING, v.121, pp.185 - 194
Abstract
In this paper, the problem of delay-dependent stability for discrete-time neural networks with time-varying delays is investigated. By constructing a newly augmented Lyapunov-Krasovskii functional, a sufficient condition for guaranteeing the asymptotic stability of the concerned network is derived in the framework of linear matrix inequalities. Also, a further improved stability condition is developed by proposing a new activation condition which has not been considered in the literature. Two numerical examples are given to illustrate the effectiveness of the proposed methods. (C) 2013 Elsevier B.V. All rights reserved.
URI
http://hdl.handle.net/YU.REPOSITORY/28139http://dx.doi.org/10.1016/j.neucom.2013.04.026
ISSN
0925-2312
Appears in Collections:
공과대학 > 전기공학과 > Articles
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