Simplifying Complex Network Stability Analysis via Hierarchical Node Aggregation and Optimal Periodic Control.

Xiong, W; Yu, X; Liu, C; Wen, G; Wen, S

Simplifying Complex Network Stability Analysis via Hierarchical Node Aggregation and Optimal Periodic Control.

Xiong, W Yu, X Liu, C Wen, G Wen, S

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Publisher:: Institute of Electrical and Electronics Engineers
Publication Type:: Journal Article
Citation:: IEEE Transactions on Neural Networks and Learning Systems, 2021, 32, (7), pp. 3098-3107
Issue Date:: 2021-07-30

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Field	Value	Language
dc.contributor.author	Xiong, W
dc.contributor.author	Yu, X
dc.contributor.author	Liu, C
dc.contributor.author	Wen, G
dc.contributor.author	Wen, S https://orcid.org/0000-0001-8077-7001
dc.date.accessioned	2022-04-27T06:57:18Z
dc.date.available	2022-04-27T06:57:18Z
dc.date.issued	2021-07-30
dc.identifier.citation	IEEE Transactions on Neural Networks and Learning Systems, 2021, 32, (7), pp. 3098-3107
dc.identifier.issn	1045-9227
dc.identifier.issn	2162-2388
dc.identifier.uri	http://hdl.handle.net/10453/156664
dc.description.abstract	In this study, the stability of a hierarchical network with delayed output is discussed by applying a kind of optimal periodic control. To reduce the number of the nodes of the original hierarchical network, an aggregation algorithm is first presented to take some nodes with the same information as an aggregated node. Furthermore, the stability of the original hierarchical network can be guaranteed by the optimal periodic control of the aggregated hierarchical network. Then, an optimal control scheme is proposed to reduce the bandwidth waste in information transmission. In the control scheme, the time sequence is separated into two parts: the deterministic segment and the dynamic segment. With the optimal control scheme, two targets are achieved: 1) the outputs of the original and aggregated hierarchical system are both asymptotically stable and 2) the nodes with slow convergent rate can catch up with the convergence speeds of other nodes.
dc.format	Print-Electronic
dc.language	eng
dc.publisher	Institute of Electrical and Electronics Engineers
dc.relation.ispartof	IEEE Transactions on Neural Networks and Learning Systems
dc.relation.isbasedon	10.1109/TNNLS.2020.3009436
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject.classification	Artificial Intelligence & Image Processing
dc.title	Simplifying Complex Network Stability Analysis via Hierarchical Node Aggregation and Optimal Periodic Control.
dc.type	Journal Article
utslib.citation.volume	32
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	*
pubs.consider-herdc	false
dc.date.updated	2022-04-27T06:57:16Z
pubs.issue	7
pubs.publication-status	Published
pubs.volume	32
utslib.citation.issue	7

Abstract:

In this study, the stability of a hierarchical network with delayed output is discussed by applying a kind of optimal periodic control. To reduce the number of the nodes of the original hierarchical network, an aggregation algorithm is first presented to take some nodes with the same information as an aggregated node. Furthermore, the stability of the original hierarchical network can be guaranteed by the optimal periodic control of the aggregated hierarchical network. Then, an optimal control scheme is proposed to reduce the bandwidth waste in information transmission. In the control scheme, the time sequence is separated into two parts: the deterministic segment and the dynamic segment. With the optimal control scheme, two targets are achieved: 1) the outputs of the original and aggregated hierarchical system are both asymptotically stable and 2) the nodes with slow convergent rate can catch up with the convergence speeds of other nodes.

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http://hdl.handle.net/10453/156664