Improved Criteria on Delay-Dependent Stability for Discrete-Time Neural Networks with Interval Time-Varying Delays

Title
Improved Criteria on Delay-Dependent Stability for Discrete-Time Neural Networks with Interval Time-Varying Delays
Author(s)
박주현O.M. Kwon[O.M. Kwon]S.M. Lee[S.M. Lee]E.J. Cha[E.J. Cha]M.J. Park[M.J. Park]
Keywords
EXPONENTIAL STABILITY; ROBUST STABILITY; SYSTEMS
Issue Date
201212
Publisher
HINDAWI PUBLISHING CORPORATION
Citation
ABSTRACT AND APPLIED ANALYSIS
Abstract
The purpose of this paper is to investigate the delay-dependent stability analysis for discrete-time neural networks with interval time-varying delays. Based on Lyapunov method, improved delay-dependent criteria for the stability of the networks are derived in terms of linear matrix inequalities (LMIs) by constructing a suitable Lyapunov-Krasovskii functional and utilizing reciprocally convex approach. Also, a new activation condition which has not been considered in the literature is proposed and utilized for derivation of stability criteria. Two numerical examples are given to illustrate the effectiveness of the proposed method.
URI
http://hdl.handle.net/YU.REPOSITORY/26727http://dx.doi.org/10.1155/2012/285931
ISSN
1085-3375
Appears in Collections:
공과대학 > 전기공학과 > Articles
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