Finite-time synchronization of T-S fuzzy memristive neural networks with time delay

Gong, S; Guo, Z; Wen, S

Finite-time synchronization of T-S fuzzy memristive neural networks with time delay

Gong, S Guo, Z Wen, S

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Publisher:: Elsevier
Publication Type:: Journal Article
Citation:: Fuzzy Sets and Systems, 2022
Issue Date:: 2022-01-01

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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.date.accessioned	2023-01-30T07:22:24Z
dc.date.available	2023-01-30T07:22:24Z
dc.date.issued	2022-01-01
dc.identifier.citation	Fuzzy Sets and Systems, 2022
dc.identifier.issn	0165-0114
dc.identifier.uri	http://hdl.handle.net/10453/165614
dc.description.abstract	This paper focuses on the study of synchronization problem for T-S fuzzy memristive neural networks with time delay. First, a delay-independent nonlinear fuzzy control is designed. Second, under the designed fuzzy control, two kinds of finite-time synchronization criteria are obtained by comparison method and Lyapunov function method, respectively. Furthermore, the settling time is estimated. Finally, a numerical simulation example is provided to demonstrate the effectiveness and feasibility of the theoretical results, and an application of the obtained theories is also given in the pseudorandom number generator (PRNG).
dc.language	en
dc.publisher	Elsevier
dc.relation.ispartof	Fuzzy Sets and Systems
dc.relation.isbasedon	10.1016/j.fss.2022.10.013
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0101 Pure Mathematics, 0801 Artificial Intelligence and Image Processing
dc.subject.classification	Artificial Intelligence & Image Processing
dc.title	Finite-time synchronization of T-S fuzzy memristive neural networks with time delay
dc.type	Journal Article
utslib.for	0101 Pure Mathematics
utslib.for	0801 Artificial Intelligence and Image Processing
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	2023-01-30T07:22:22Z
pubs.publication-status	Published

Abstract:

This paper focuses on the study of synchronization problem for T-S fuzzy memristive neural networks with time delay. First, a delay-independent nonlinear fuzzy control is designed. Second, under the designed fuzzy control, two kinds of finite-time synchronization criteria are obtained by comparison method and Lyapunov function method, respectively. Furthermore, the settling time is estimated. Finally, a numerical simulation example is provided to demonstrate the effectiveness and feasibility of the theoretical results, and an application of the obtained theories is also given in the pseudorandom number generator (PRNG).

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http://hdl.handle.net/10453/165614