Synchronization control for memristive high-order competitive neural networks with time-varying delay

Gong, S; Guo, Z; Wen, S; Huang, T

Synchronization control for memristive high-order competitive neural networks with time-varying delay

Gong, S Guo, Z Wen, S

Huang, T

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Publisher:: ELSEVIER
Publication Type:: Journal Article
Citation:: Neurocomputing, 2019, 363, pp. 295-305
Issue Date:: 2019-10-21

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Field	Value	Language
dc.contributor.author	Gong, S
dc.contributor.author	Guo, Z
dc.contributor.author	Wen, S https://orcid.org/0000-0001-8077-7001
dc.contributor.author	Huang, T
dc.date.accessioned	2022-07-18T06:01:26Z
dc.date.available	2022-07-18T06:01:26Z
dc.date.issued	2019-10-21
dc.identifier.citation	Neurocomputing, 2019, 363, pp. 295-305
dc.identifier.issn	0925-2312
dc.identifier.issn	1872-8286
dc.identifier.uri	http://hdl.handle.net/10453/159003
dc.description.abstract	This paper concerns the synchronization problem of memristive high-order competitive neural networks with time-varying delay. First, a novel control scheme with a linear term and a discontinuous term is proposed. Then, based on the Lyapunov stability theory, several criteria with algebraic form or matrix form are derived to ensure global exponential synchronization of the networks by adopting some inequality techniques. Finally, two numerical examples are presented to substantiate the effectiveness of the results.
dc.language	English
dc.publisher	ELSEVIER
dc.relation.ispartof	Neurocomputing
dc.relation.isbasedon	10.1016/j.neucom.2019.06.049
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	08 Information and Computing Sciences, 09 Engineering, 17 Psychology and Cognitive Sciences
dc.subject.classification	Artificial Intelligence & Image Processing
dc.title	Synchronization control for memristive high-order competitive neural networks with time-varying delay
dc.type	Journal Article
utslib.citation.volume	363
utslib.for	08 Information and Computing Sciences
utslib.for	09 Engineering
utslib.for	17 Psychology and Cognitive Sciences
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - AAII - Australian Artificial Intelligence Institute
utslib.copyright.status	closed_access	*
dc.date.updated	2022-07-18T06:01:24Z
pubs.publication-status	Published
pubs.volume	363

Abstract:

This paper concerns the synchronization problem of memristive high-order competitive neural networks with time-varying delay. First, a novel control scheme with a linear term and a discontinuous term is proposed. Then, based on the Lyapunov stability theory, several criteria with algebraic form or matrix form are derived to ensure global exponential synchronization of the networks by adopting some inequality techniques. Finally, two numerical examples are presented to substantiate the effectiveness of the results.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/159003