Mittag-Leffler stability of fractional-order quaternion-valued memristive neural networks with generalized piecewise constant argument.

Wang, J; Zhu, S; Liu, X; Wen, S

Mittag-Leffler stability of fractional-order quaternion-valued memristive neural networks with generalized piecewise constant argument.

Wang, J Zhu, S Liu, X Wen, S

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Publisher:: PERGAMON-ELSEVIER SCIENCE LTD
Publication Type:: Journal Article
Citation:: Neural Netw, 2023, 162, pp. 175-185
Issue Date:: 2023-05

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Field	Value	Language
dc.contributor.author	Wang, J
dc.contributor.author	Zhu, S
dc.contributor.author	Liu, X
dc.contributor.author	Wen, S https://orcid.org/0000-0001-8077-7001
dc.date.accessioned	2024-01-16T21:29:37Z
dc.date.available	2023-02-21
dc.date.available	2024-01-16T21:29:37Z
dc.date.issued	2023-05
dc.identifier.citation	Neural Netw, 2023, 162, pp. 175-185
dc.identifier.issn	0893-6080
dc.identifier.issn	1879-2782
dc.identifier.uri	http://hdl.handle.net/10453/174648
dc.description.abstract	This paper studies the global Mittag-Leffler (M-L) stability problem for fractional-order quaternion-valued memristive neural networks (FQVMNNs) with generalized piecewise constant argument (GPCA). First, a novel lemma is established, which is used to investigate the dynamic behaviors of quaternion-valued memristive neural networks (QVMNNs). Second, by using the theories of differential inclusion, set-valued mapping, and Banach fixed point, several sufficient criteria are derived to ensure the existence and uniqueness (EU) of the solution and equilibrium point for the associated systems. Then, by constructing Lyapunov functions and employing some inequality techniques, a set of criteria are proposed to ensure the global M-L stability of the considered systems. The obtained results in this paper not only extends previous works, but also provides new algebraic criteria with a larger feasible range. Finally, two numerical examples are introduced to illustrate the effectiveness of the obtained results.
dc.format	Print-Electronic
dc.language	eng
dc.publisher	PERGAMON-ELSEVIER SCIENCE LTD
dc.relation.ispartof	Neural Netw
dc.relation.isbasedon	10.1016/j.neunet.2023.02.030
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject.classification	Artificial Intelligence & Image Processing
dc.subject.classification	4602 Artificial intelligence
dc.subject.classification	4611 Machine learning
dc.subject.classification	4905 Statistics
dc.title	Mittag-Leffler stability of fractional-order quaternion-valued memristive neural networks with generalized piecewise constant argument.
dc.type	Journal Article
utslib.citation.volume	162
utslib.location.activity	United States
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	2024-01-16T21:29:36Z
pubs.publication-status	Published
pubs.volume	162

Abstract:

This paper studies the global Mittag-Leffler (M-L) stability problem for fractional-order quaternion-valued memristive neural networks (FQVMNNs) with generalized piecewise constant argument (GPCA). First, a novel lemma is established, which is used to investigate the dynamic behaviors of quaternion-valued memristive neural networks (QVMNNs). Second, by using the theories of differential inclusion, set-valued mapping, and Banach fixed point, several sufficient criteria are derived to ensure the existence and uniqueness (EU) of the solution and equilibrium point for the associated systems. Then, by constructing Lyapunov functions and employing some inequality techniques, a set of criteria are proposed to ensure the global M-L stability of the considered systems. The obtained results in this paper not only extends previous works, but also provides new algebraic criteria with a larger feasible range. Finally, two numerical examples are introduced to illustrate the effectiveness of the obtained results.

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http://hdl.handle.net/10453/174648