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

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DC Field	Value	Language
dc.contributor.author	Arthi G	-
dc.contributor.author	Park, J H	-
dc.contributor.author	Jung, H Y	-
dc.contributor.author	Yoo, J H	-
dc.date.accessioned	2020-08-25T05:25:12Z	-
dc.date.available	2020-08-25T05:25:12Z	-
dc.date.issued	2015-04-22	-
dc.identifier.issn	0925-2312	-
dc.identifier.uri	https://doi.org/10.1016/j.neucom.2014.11.061	-
dc.identifier.uri	http://localhost:8080/xmlui/handle/123456789/1076	-
dc.description.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	en_US
dc.language.iso	en	en_US
dc.publisher	Neurocomputing, ELSEVIER	en_US
dc.subject	Stochastic differential equations	en_US
dc.subject	Neuron system	en_US
dc.subject	Neutral equations	en_US
dc.subject	Global exponential stability	en_US
dc.title	EXPONENTIAL STABILITY CRITERIA FOR A NEUTRAL TYPE STOCHASTIC SINGLE NEURON SYSTEM WITH TIME-VARYING DELAYS	en_US
dc.type	Article	en_US
Appears in Collections:	International Journals

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