Exponential stability criteria for a neutral type stochastic single neuron system with time-varying delays

Title
Exponential stability criteria for a neutral type stochastic single neuron system with time-varying delays
Author(s)
정호열가네산아티박주현유준혁[유준혁]
Keywords
DIFFERENTIAL-EQUATIONS; ASYMPTOTIC STABILITY; NETWORKS; CONVERGENCE; RESONANCE; MODEL
Issue Date
201504
Publisher
ELSEVIER SCIENCE BV
Citation
NEUROCOMPUTING, v.154, pp.317 - 324
Abstract
In this paper, the issue of global exponential stability for a neutral type single neuron system with stochastic effects is investigated. Based on the linear matrix inequality (LMI) approach together with a novel Lyapunov-Krasovskii functional and stochastic analysis theory, sufficient conditions are derived to ensure that the considered system with time-varying delays is globally exponentially stable. Numerical examples are provided to demonstrate the efficiency and less conservatism of the derived theoretical results. (C) 2014 Elsevier B.V. All rights reserved.
URI
http://hdl.handle.net/YU.REPOSITORY/32718http://dx.doi.org/10.1016/j.neucom.2014.11.061
ISSN
0925-2312
Appears in Collections:
공과대학 > 모바일정보통신공학과 > Articles
공과대학 > 전기공학과 > Articles
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