Synchronization of fractional-order spatiotemporal complex networks with boundary communication

Yang, Y; Hu, C; Yu, J; Jiang, H; Wen, S

Synchronization of fractional-order spatiotemporal complex networks with boundary communication

Yang, Y Hu, C Yu, J Jiang, H Wen, S

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Publisher:: Elsevier
Publication Type:: Journal Article
Citation:: Neurocomputing, 2021, 450, pp. 197-207
Issue Date:: 2021-08-25

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Field	Value	Language
dc.contributor.author	Yang, Y
dc.contributor.author	Hu, C
dc.contributor.author	Yu, J
dc.contributor.author	Jiang, H
dc.contributor.author	Wen, S https://orcid.org/0000-0001-8077-7001
dc.date.accessioned	2022-05-23T05:06:20Z
dc.date.available	2022-05-23T05:06:20Z
dc.date.issued	2021-08-25
dc.identifier.citation	Neurocomputing, 2021, 450, pp. 197-207
dc.identifier.issn	0925-2312
dc.identifier.issn	1872-8286
dc.identifier.uri	http://hdl.handle.net/10453/157632
dc.description.abstract	This article is dedicated to the synchronization problem of fractional-order spatiotemporal networks with boundary coupling. Above all, instead of the traditional coupling form at the whole space, a type of boundary communication mechanism is proposed for fractional-order spatiotemporal networks, where nodes interact each other only at the spatial boundary. Subsequently, based on fractional-order inequalities and various analytical skills, some synchronization criteria are derived for the addressed networks with boundary constant weights or time-varying weights. Particularly, an adaptive scheme and its pinning form are designed to update time-varying coupling weights only based on the states information at the boundary position, which are more effective and convenient compared to the existing adaptive strategies dependent of states information in whole space. In addition, a rigorous theoretical analysis is developed for fractional-order adaptive strategy, which provides a new analytic method for adaptive control of fractional-order models. Lastly, the theoretical analysis is confirmed by a numerical example.
dc.language	en
dc.publisher	Elsevier
dc.relation.ispartof	Neurocomputing
dc.relation.isbasedon	10.1016/j.neucom.2021.04.008
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 of fractional-order spatiotemporal complex networks with boundary communication
dc.type	Journal Article
utslib.citation.volume	450
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	*
pubs.consider-herdc	false
dc.date.updated	2022-05-23T05:06:19Z
pubs.publication-status	Published
pubs.volume	450

Abstract:

This article is dedicated to the synchronization problem of fractional-order spatiotemporal networks with boundary coupling. Above all, instead of the traditional coupling form at the whole space, a type of boundary communication mechanism is proposed for fractional-order spatiotemporal networks, where nodes interact each other only at the spatial boundary. Subsequently, based on fractional-order inequalities and various analytical skills, some synchronization criteria are derived for the addressed networks with boundary constant weights or time-varying weights. Particularly, an adaptive scheme and its pinning form are designed to update time-varying coupling weights only based on the states information at the boundary position, which are more effective and convenient compared to the existing adaptive strategies dependent of states information in whole space. In addition, a rigorous theoretical analysis is developed for fractional-order adaptive strategy, which provides a new analytic method for adaptive control of fractional-order models. Lastly, the theoretical analysis is confirmed by a numerical example.

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http://hdl.handle.net/10453/157632