New and improved results on stability of static neural networks with interval time-varying delays

Title
New and improved results on stability of static neural networks with interval 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
DEPENDENT STABILITY; LINEAR-SYSTEMS
Issue Date
201407
Publisher
ELSEVIER SCIENCE INC
Citation
APPLIED MATHEMATICS AND COMPUTATION, v.239, pp.346 - 357
Abstract
In this paper, the problem of stability analysis for static neural networks with interval time-varying delays is considered. By the consideration of new augmented Lyapunov functionals, new and improved delay-dependent stability criteria to guarantee the asymptotic stability of the concerned networks are proposed with the framework of linear matrix inequalities (LMIs), which can be solved easily by standard numerical packages. The enhancement of the feasible region of the proposed criteria is shown via two numerical examples by the comparison of maximum delay bounds. (C) 2014 Elsevier Inc. All rights reserved.
URI
http://hdl.handle.net/YU.REPOSITORY/31601http://dx.doi.org/10.1016/j.amc.2014.04.089
ISSN
0096-3003
Appears in Collections:
공과대학 > 전기공학과 > Articles
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