A study on H-infinity state estimation of static neural networks with time-varying delays

Title
A study on H-infinity state estimation of static neural networks with time-varying delays
Author(s)
박주현S.M. Lee[S.M. Lee]Y. Liu[Y. Liu]O.M. Kwon[O.M. Kwon]
Keywords
DISTRIBUTED DELAYS; DEPENDENT STABILITY; DISCRETE; DESIGN
Issue Date
201401
Publisher
ELSEVIER SCIENCE INC
Citation
APPLIED MATHEMATICS AND COMPUTATION, v.226, pp.589 - 597
Abstract
This paper studies the problem of H-infinity state estimation for static neural networks with time-varying delay. By construction of a suitable Lyapunov-Krasovskii functional, some improved delay-dependent conditions are established such that the error system is globally exponentially stable with a decay rate and a prescribed H-infinity performance is guaranteed. In order to get less conservative results of the state estimation condition, zero equalities and reciprocally convex approach are employed. The estimator gain matrix can be obtained in terms of the solution to linear matrix inequalities. Numerical examples are provided to illustrate the effectiveness and performance of the developed Method. (C) 2013 Elsevier Inc. All rights reserved.
URI
http://hdl.handle.net/YU.REPOSITORY/33594http://dx.doi.org/10.1016/j.amc.2013.10.075
ISSN
0096-3003
Appears in Collections:
공과대학 > 전기공학과 > Articles
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