Event-Triggered Finite-Time Synchronization Control for Quaternion-Valued Memristive Neural Networks by an Non-Decomposition Method

Ping, J; Zhu, S; Shi, M; Wu, S; Shen, M; Liu, X; Wen, S

Event-Triggered Finite-Time Synchronization Control for Quaternion-Valued Memristive Neural Networks by an Non-Decomposition Method

Ping, J Zhu, S Shi, M Wu, S Shen, M Liu, X Wen, S

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Publisher:: IEEE COMPUTER SOC
Publication Type:: Journal Article
Citation:: IEEE Transactions on Network Science and Engineering, 2023, 10, (6), pp. 3609-3619
Issue Date:: 2023-11-01

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Field	Value	Language
dc.contributor.author	Ping, J
dc.contributor.author	Zhu, S
dc.contributor.author	Shi, M
dc.contributor.author	Wu, S
dc.contributor.author	Shen, M
dc.contributor.author	Liu, X
dc.contributor.author	Wen, S https://orcid.org/0000-0001-8077-7001
dc.date.accessioned	2024-01-16T21:14:44Z
dc.date.available	2024-01-16T21:14:44Z
dc.date.issued	2023-11-01
dc.identifier.citation	IEEE Transactions on Network Science and Engineering, 2023, 10, (6), pp. 3609-3619
dc.identifier.issn	2327-4697
dc.identifier.issn	2327-4697
dc.identifier.uri	http://hdl.handle.net/10453/174624
dc.description.abstract	Applying the event-triggered control, this article discusses the finite-time synchronization issue of quaternion-valued memristive neural networks (QVMNNs) with time-varying delays. By employing the improved one norm and sign function of quaternion, the QVMNNs can be analyzed as an entirety without any decomposition. To relieve the communication pressure, a proper event-triggered controller is designed, then the event-triggered conditions and some criteria are also established to guarantee finite-time synchronization. Moreover, the synchronization time is estimated by direct analysis, and the positive lower bound of the inter-event time is obtained to get rid of the Zeno behavior. In addition, according to the acquired event-triggered scheme, a self-triggered scheme is further provided to refrain from continuous detection. Ultimately, the validity of the obtained theoretical results is demonstrated by a numerical simulation.
dc.language	English
dc.publisher	IEEE COMPUTER SOC
dc.relation.ispartof	IEEE Transactions on Network Science and Engineering
dc.relation.isbasedon	10.1109/TNSE.2023.3268101
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Event-Triggered Finite-Time Synchronization Control for Quaternion-Valued Memristive Neural Networks by an Non-Decomposition Method
dc.type	Journal Article
utslib.citation.volume	10
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	2024-01-16T21:14:43Z
pubs.issue	6
pubs.publication-status	Published
pubs.volume	10
utslib.citation.issue	6

Abstract:

Applying the event-triggered control, this article discusses the finite-time synchronization issue of quaternion-valued memristive neural networks (QVMNNs) with time-varying delays. By employing the improved one norm and sign function of quaternion, the QVMNNs can be analyzed as an entirety without any decomposition. To relieve the communication pressure, a proper event-triggered controller is designed, then the event-triggered conditions and some criteria are also established to guarantee finite-time synchronization. Moreover, the synchronization time is estimated by direct analysis, and the positive lower bound of the inter-event time is obtained to get rid of the Zeno behavior. In addition, according to the acquired event-triggered scheme, a self-triggered scheme is further provided to refrain from continuous detection. Ultimately, the validity of the obtained theoretical results is demonstrated by a numerical simulation.

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http://hdl.handle.net/10453/174624