Interval Bipartite Synchronization of Delayed Nonlinear Neural Networks With Signed Graphs

Sun, W; Guo, W; Li, B; Wen, S; Wu, X

Interval Bipartite Synchronization of Delayed Nonlinear Neural Networks With Signed Graphs

Sun, W Guo, W Li, B Wen, S

Wu, X

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Publisher:: Institute of Electrical and Electronics Engineers (IEEE)
Publication Type:: Journal Article
Citation:: IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2022, 53, (3), pp. 1723-1733
Issue Date:: 2022-01-01

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Field	Value	Language
dc.contributor.author	Sun, W
dc.contributor.author	Guo, W
dc.contributor.author	Li, B
dc.contributor.author	Wen, S https://orcid.org/0000-0001-8077-7001
dc.contributor.author	Wu, X
dc.date.accessioned	2023-02-28T04:18:21Z
dc.date.available	2023-02-28T04:18:21Z
dc.date.issued	2022-01-01
dc.identifier.citation	IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2022, 53, (3), pp. 1723-1733
dc.identifier.issn	2168-2216
dc.identifier.issn	2168-2232
dc.identifier.uri	http://hdl.handle.net/10453/166555
dc.description.abstract	The cooperation of linear multiagent systems (MASs) in the signed graphs has received wide attention. However, time delays and nonlinearity are ignored. This article deals with the cooperation behavior, especially interval bipartite synchronization (IBS) of delayed nonlinear neural networks (NNs) with signed graphs. A generalized matrix is proposed for the construction of the Lyapunov functionals, establishing sufficient conditions in a linear matrix inequality related to the coupling strength, the delays, and the network structure. It suggests that the negative rooted cycles and the negative nonrooted cycles take an important part in stabilizing delayed nonlinear NNs and leading to their diversity, and time delays, especially communication delays, significantly impact cooperation performance. Numerical examples are employed to validate our derived results.
dc.language	en
dc.publisher	Institute of Electrical and Electronics Engineers (IEEE)
dc.relation.ispartof	IEEE Transactions on Systems, Man, and Cybernetics: Systems
dc.relation.isbasedon	10.1109/TSMC.2022.3206219
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	08 Information and Computing Sciences, 09 Engineering
dc.subject.classification	Artificial Intelligence & Image Processing
dc.title	Interval Bipartite Synchronization of Delayed Nonlinear Neural Networks With Signed Graphs
dc.type	Journal Article
utslib.citation.volume	53
utslib.for	08 Information and Computing Sciences
utslib.for	09 Engineering
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	2023-02-28T04:18:20Z
pubs.issue	3
pubs.publication-status	Published
pubs.volume	53
utslib.citation.issue	3

Abstract:

The cooperation of linear multiagent systems (MASs) in the signed graphs has received wide attention. However, time delays and nonlinearity are ignored. This article deals with the cooperation behavior, especially interval bipartite synchronization (IBS) of delayed nonlinear neural networks (NNs) with signed graphs. A generalized matrix is proposed for the construction of the Lyapunov functionals, establishing sufficient conditions in a linear matrix inequality related to the coupling strength, the delays, and the network structure. It suggests that the negative rooted cycles and the negative nonrooted cycles take an important part in stabilizing delayed nonlinear NNs and leading to their diversity, and time delays, especially communication delays, significantly impact cooperation performance. Numerical examples are employed to validate our derived results.

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http://hdl.handle.net/10453/166555