IMPROVED RESULTS ON STABILITY ANALYSIS OF NEURAL NETWORKS WITH TIME-VARYING DELAYS: NOVEL DELAY-DEPENDENT CRITERIA

Title
IMPROVED RESULTS ON STABILITY ANALYSIS OF NEURAL NETWORKS WITH TIME-VARYING DELAYS: NOVEL DELAY-DEPENDENT CRITERIA
Author(s)
박주현O.M. Kwon[O.M. Kwon]S.M. Lee[S.M. Lee]
Keywords
GLOBAL ASYMPTOTIC STABILITY; NEUTRAL-TYPE; SYNCHRONIZATION; SYSTEMS; MODEL
Issue Date
201003
Publisher
WORLD SCIENTIFIC PUBL CO PTE LTD
Citation
MODERN PHYSICS LETTERS B, v.24, no.8, pp.775 - 789
Abstract
In this paper, the problem of stability analysis of neural networks with discrete time-varying delays is considered. By constructing a new Lyapunov functional and some novel analysis techniques, new delay-dependent criteria for checking the asymptotic stability of the neural networks are established. The criteria are presented in terms of linear matrix inequalities, which can be easily solved and checked by various convex optimization algorithms. Three numerical examples are included to show the superiority of our results.
URI
http://hdl.handle.net/YU.REPOSITORY/22782http://dx.doi.org/10.1142/S0217984910022858
ISSN
0217-9849
Appears in Collections:
공과대학 > 전기공학과 > Articles
Files in This Item:
There are no files associated with this item.
Export
RIS (EndNote)
XLS (Excel)
XML


qrcode

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

BROWSE