State estimation for neural neutral-type networks with mixed time-varying delays and Markovian jumping parameters

Title
State estimation for neural neutral-type networks with mixed time-varying delays and Markovian jumping parameters
Author(s)
정호열박주현락쉬마난[락쉬마난]P. Balasubramaniam[P. Balasubramaniam]
Keywords
GLOBAL EXPONENTIAL STABILITY; DEPENDENT STABILITY; CRITERIA
Issue Date
201210
Publisher
IOP PUBLISHING LTD
Citation
CHINESE PHYSICS B, v.21, no.10
Abstract
This paper is concerned with a delay-dependent state estimator for neutral-type neural networks with mixed time-varying delays and Markovian jumping parameters. The addressed neural networks have a finite number of modes, and the modes may jump from one to another according to a Markov process. By construction of a suitable Lyapunov-Krasovskii functional, a delay-dependent condition is developed to estimate the neuron states through available output measurements such that the estimation error system is globally asymptotically stable in a mean square. The criterion is formulated in terms of a set of linear matrix inequalities (LMIs), which can be checked efficiently by use of some standard numerical packages.
URI
http://hdl.handle.net/YU.REPOSITORY/27170http://dx.doi.org/10.1088/1674-1056/21/10/100205
ISSN
1674-1056
Appears in Collections:
공과대학 > 모바일정보통신공학과 > Articles
공과대학 > 전기공학과 > Articles
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