Lag projective synchronization of nonidentical fractional delayed memristive neural networks

Ding, Z; Chen, C; Wen, S; Li, S; Wang, L

Lag projective synchronization of nonidentical fractional delayed memristive neural networks

Ding, Z Chen, C Wen, S

Li, S Wang, L

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Publisher:: Elsevier BV
Publication Type:: Journal Article
Citation:: Neurocomputing, 2022, 469, pp. 138-150
Issue Date:: 2022-01-16

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Field	Value	Language
dc.contributor.author	Ding, Z
dc.contributor.author	Chen, C
dc.contributor.author	Wen, S https://orcid.org/0000-0001-8077-7001
dc.contributor.author	Li, S
dc.contributor.author	Wang, L
dc.date.accessioned	2023-02-28T03:54:12Z
dc.date.available	2023-02-28T03:54:12Z
dc.date.issued	2022-01-16
dc.identifier.citation	Neurocomputing, 2022, 469, pp. 138-150
dc.identifier.issn	0925-2312
dc.identifier.issn	1872-8286
dc.identifier.uri	http://hdl.handle.net/10453/166540
dc.description.abstract	In this paper, lag projective synchronization of nonidentical fractional delayed memristive neural networks (NFDMNN) is investigated. Due to the existence of memristor, the analysis is based on the theory of differential equations with discontinuous right-hand side proposed by Filippov. A novel controller with fractional integral sliding-mode surface is devised firstly. Successively, some sufficient criteria ensuring lag projective synchronization of NFDMNN are obtained, depending on the fractional calculus inequalities and Lyapunov direct method. Moreover, the related results improve and enrich previous synchronization works. Lastly, the validity of conclusions is verified through a simulation example.
dc.language	en
dc.publisher	Elsevier BV
dc.relation	National Natural Science Foundation of China61673187
dc.relation.ispartof	Neurocomputing
dc.relation.isbasedon	10.1016/j.neucom.2021.10.061
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	Lag projective synchronization of nonidentical fractional delayed memristive neural networks
dc.type	Journal Article
utslib.citation.volume	469
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	2023-02-28T03:54:11Z
pubs.publication-status	Published
pubs.volume	469

Abstract:

In this paper, lag projective synchronization of nonidentical fractional delayed memristive neural networks (NFDMNN) is investigated. Due to the existence of memristor, the analysis is based on the theory of differential equations with discontinuous right-hand side proposed by Filippov. A novel controller with fractional integral sliding-mode surface is devised firstly. Successively, some sufficient criteria ensuring lag projective synchronization of NFDMNN are obtained, depending on the fractional calculus inequalities and Lyapunov direct method. Moreover, the related results improve and enrich previous synchronization works. Lastly, the validity of conclusions is verified through a simulation example.

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http://hdl.handle.net/10453/166540