Improved Delay-dependent Robust Stability Analysis for Neutral-type Uncertain Neural Networks with Markovian jumping Parameters and Time-varying Delays

Title
Improved Delay-dependent Robust Stability Analysis for Neutral-type Uncertain Neural Networks with Markovian jumping Parameters and Time-varying Delays
Author(s)
박주현J. Xia[J. Xia]H. Zeng[H. Zeng]
Keywords
GLOBAL ASYMPTOTIC STABILITY; VEHICLE SUSPENSION SYSTEMS; SAMPLED-DATA CONTROL; H-INFINITY CONTROL; EXPONENTIAL STABILITY; DISTRIBUTED DELAYS; MIXED DELAYS; DISCRETE; CRITERIA
Issue Date
201502
Publisher
ELSEVIER SCIENCE BV
Citation
NEUROCOMPUTING, v.149, pp.1198 - 1205
Abstract
This paper deals with the problem of robust stochastic stability analysis for a class of neutral-type uncertain neural networks with Markovian jumping parameters and time-varying delays. By introducing an novel mode-dependent Augmented Lyapunov-Krasovskii functional with delay partitioning and Wirtinger-based integral inequality techniques, some improved delay-dependent stochastically stable conditions are proposed in the form of LMIs. Numerical simulations are provided to show the effectiveness and less conservatism of the results. (c) 2014 Elsevier B.V. All rights reserved.
URI
http://hdl.handle.net/YU.REPOSITORY/33449http://dx.doi.org/10.1016/j.neucom.2014.09.008
ISSN
0925-2312
Appears in Collections:
공과대학 > 전기공학과 > Articles
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