New Results on Finite-Time Synchronization Control of Chaotic Memristor-Based Inertial Neural Networks with Time-Varying Delays

Wang, J; Tian, Y; Hua, L; Shi, K; Zhong, S; Wen, S

New Results on Finite-Time Synchronization Control of Chaotic Memristor-Based Inertial Neural Networks with Time-Varying Delays

Wang, J Tian, Y Hua, L Shi, K Zhong, S Wen, S

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Publisher:: MDPI
Publication Type:: Journal Article
Citation:: Mathematics, 2023, 11, (3), pp. 684
Issue Date:: 2023-02-01

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Field	Value	Language
dc.contributor.author	Wang, J
dc.contributor.author	Tian, Y
dc.contributor.author	Hua, L
dc.contributor.author	Shi, K
dc.contributor.author	Zhong, S
dc.contributor.author	Wen, S https://orcid.org/0000-0001-8077-7001
dc.date.accessioned	2023-03-13T12:50:52Z
dc.date.available	2023-03-13T12:50:52Z
dc.date.issued	2023-02-01
dc.identifier.citation	Mathematics, 2023, 11, (3), pp. 684
dc.identifier.issn	2227-7390
dc.identifier.issn	2227-7390
dc.identifier.uri	http://hdl.handle.net/10453/167167
dc.description.abstract	In this work, we are concerned with the finite-time synchronization (FTS) control issue of the drive and response delayed memristor-based inertial neural networks (MINNs). Firstly, a novel finite-time stability lemma is developed, which is different from the existing finite-time stability criteria and extends the previous results. Secondly, by constructing an appropriate Lyapunov function, designing effective delay-dependent feedback controllers and combining the finite-time control theory with a new non-reduced order method (NROD), several novel theoretical criteria to ensure the FTS for the studied MINNs are provided. In addition, the obtained theoretical results are established in a more general framework than the previous works and widen the application scope. Lastly, we illustrate the practicality and validity of the theoretical results via some numerical examples.
dc.language	en
dc.publisher	MDPI
dc.relation.ispartof	Mathematics
dc.relation.isbasedon	10.3390/math11030684
dc.rights	info:eu-repo/semantics/openAccess
dc.title	New Results on Finite-Time Synchronization Control of Chaotic Memristor-Based Inertial Neural Networks with Time-Varying Delays
dc.type	Journal Article
utslib.citation.volume	11
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	open_access	*
dc.date.updated	2023-03-13T12:50:51Z
pubs.issue	3
pubs.publication-status	Published
pubs.volume	11
utslib.citation.issue	3

Abstract:

In this work, we are concerned with the finite-time synchronization (FTS) control issue of the drive and response delayed memristor-based inertial neural networks (MINNs). Firstly, a novel finite-time stability lemma is developed, which is different from the existing finite-time stability criteria and extends the previous results. Secondly, by constructing an appropriate Lyapunov function, designing effective delay-dependent feedback controllers and combining the finite-time control theory with a new non-reduced order method (NROD), several novel theoretical criteria to ensure the FTS for the studied MINNs are provided. In addition, the obtained theoretical results are established in a more general framework than the previous works and widen the application scope. Lastly, we illustrate the practicality and validity of the theoretical results via some numerical examples.

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http://hdl.handle.net/10453/167167