Improved approaches to stability criteria for neural networks with time-varying delays

Title
Improved approaches to stability criteria for 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
GLOBAL ROBUST STABILITY; DEPENDENT EXPONENTIAL STABILITY; LINEAR FRACTIONAL UNCERTAINTIES; ASYMPTOTIC STABILITY; SYNCHRONIZATION ANALYSIS; DISCRETE; SYSTEMS
Issue Date
201311
Publisher
PERGAMON-ELSEVIER SCIENCE LTD
Citation
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS, v.350, no.9, pp.2710 - 2735
Abstract
In this paper, the problem of stability analysis for neural networks with time-varying delays is considered. By the use of a newly augmented Lyapunov functional and some novel techniques, sufficient conditions to guarantee the asymptotic stability of the concerned networks are established in terms of linear matrix inequalities (LMIs). Three numerical examples are given to show the improved stability region of the proposed works. (C) 2013 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
URI
http://hdl.handle.net/YU.REPOSITORY/28480http://dx.doi.org/10.1016/j.jfranklin.2013.06.014
ISSN
0016-0032
Appears in Collections:
공과대학 > 전기공학과 > Articles
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