EXPONENTIAL STABILITY CRITERIA FOR A NEUTRAL TYPE STOCHASTIC SINGLE NEURON SYSTEM WITH TIME-VARYING DELAYS

Please use this identifier to cite or link to this item: http://localhost:8080/xmlui/handle/123456789/1076

Title:	EXPONENTIAL STABILITY CRITERIA FOR A NEUTRAL TYPE STOCHASTIC SINGLE NEURON SYSTEM WITH TIME-VARYING DELAYS
Authors:	Arthi G Park, J H Jung, H Y Yoo, J H
Keywords:	Stochastic differential equations Neuron system Neutral equations Global exponential stability
Issue Date:	22-Apr-2015
Publisher:	Neurocomputing, ELSEVIER
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
URI:	https://doi.org/10.1016/j.neucom.2014.11.061 http://localhost:8080/xmlui/handle/123456789/1076
ISSN:	0925-2312
Appears in Collections:	International Journals

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