Fixed-time Synchronization of Coupled Memristive Complex-valued Neural Networks

Feng, L; Hu, C; Yu, J; Jiang, H; Wen, S

Fixed-time Synchronization of Coupled Memristive Complex-valued Neural Networks

Feng, L Hu, C Yu, J Jiang, H Wen, S

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Publisher:: Elsevier
Publication Type:: Journal Article
Citation:: Chaos, Solitons and Fractals, 2021, 148, pp. 1-12
Issue Date:: 2021-07-01

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Field	Value	Language
dc.contributor.author	Feng, L
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	2022-04-27T03:05:44Z
dc.date.available	2022-04-27T03:05:44Z
dc.date.issued	2021-07-01
dc.identifier.citation	Chaos, Solitons and Fractals, 2021, 148, pp. 1-12
dc.identifier.issn	0960-0779
dc.identifier.issn	1873-2887
dc.identifier.uri	http://hdl.handle.net/10453/156634
dc.description.abstract	By directly proposing discontinuous complex-valued controllers and constructing Lyapunov functions for complex-valued networks, this article is devoted to fixed-time (F-T) synchronization of coupled memristive complex-valued neural networks (MCNNs) with time-varying delays. Above all, a new theorem for F-T stability is established to reduce the conservatism of the existing work in terms of conditions and the estimate of stability time. Subsequently, under the framework of the complex-valued sign function, several simplified complex-valued F-T control laws are proposed by excluding the linear part in previous F-T design. Furthermore, without splitting the addressed coupled MCNNs into real-valued submodels in the theoretical analysis, several sets of conditions of F-T synchronization are obtained for coupled MCNNs by means of the theory of complex-variable functions and the improved F-T stability. Lastly, the developed control strategies and the results on F-T synchronization are verified by the presence of a numerical example.
dc.language	en
dc.publisher	Elsevier
dc.relation.ispartof	Chaos, Solitons and Fractals
dc.relation.isbasedon	10.1016/j.chaos.2021.110993
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	01 Mathematical Sciences, 08 Information and Computing Sciences, 09 Engineering
dc.subject.classification	Mathematical Physics
dc.title	Fixed-time Synchronization of Coupled Memristive Complex-valued Neural Networks
dc.type	Journal Article
utslib.citation.volume	148
utslib.for	01 Mathematical Sciences
utslib.for	08 Information and Computing Sciences
utslib.for	09 Engineering
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	2022-04-27T03:05:43Z
pubs.publication-status	Published
pubs.volume	148

Abstract:

By directly proposing discontinuous complex-valued controllers and constructing Lyapunov functions for complex-valued networks, this article is devoted to fixed-time (F-T) synchronization of coupled memristive complex-valued neural networks (MCNNs) with time-varying delays. Above all, a new theorem for F-T stability is established to reduce the conservatism of the existing work in terms of conditions and the estimate of stability time. Subsequently, under the framework of the complex-valued sign function, several simplified complex-valued F-T control laws are proposed by excluding the linear part in previous F-T design. Furthermore, without splitting the addressed coupled MCNNs into real-valued submodels in the theoretical analysis, several sets of conditions of F-T synchronization are obtained for coupled MCNNs by means of the theory of complex-variable functions and the improved F-T stability. Lastly, the developed control strategies and the results on F-T synchronization are verified by the presence of a numerical example.

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http://hdl.handle.net/10453/156634