Synchronization of discrete-time neural networks with time delays subject to missing data

Title
Synchronization of discrete-time neural networks with time delays subject to missing data
Author(s)
박주현오쟁광
Keywords
MARKOVIAN JUMPING PARAMETERS; ROBUST STATE ESTIMATION; EXPONENTIAL SYNCHRONIZATION; STABILITY ANALYSIS; VARYING DELAYS; STOCHASTIC-SYSTEMS; LINEAR-SYSTEMS; MIXED DELAYS
Issue Date
201312
Publisher
ELSEVIER SCIENCE BV
Citation
NEUROCOMPUTING, v.122, pp.418 - 424
Abstract
This paper is concerned with the problem of synchronization of discrete-time neural networks with time-delays under unreliable communication links, which are modeled as stochastic dropouts. The process of missing data satisfies a discrete-time Markov chain with two state components. By using Lyapunov functional approach, some delay-dependent synchronization criteria are first obtained and formulated in the form of linear matrix inequalities (LMIs). Then, sufficient conditions on the existence of feedback controllers are derived by employing these newly obtained synchronization criteria. The controller gains can be achieved by solving a set of LMIs. Finally, a numerical example is given to illustrate the effectiveness of the design method. (C) 2013 Elsevier B.V. All rights reserved.
URI
http://hdl.handle.net/YU.REPOSITORY/28221http://dx.doi.org/10.1016/j.neucom.2013.06.011
ISSN
0925-2312
Appears in Collections:
공과대학 > 전기공학과 > Articles
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