Topology identification of coupled neural networks with multiple weights

Wu, HY; Wang, L; Zhao, LH; Wang, JL

Topology identification of coupled neural networks with multiple weights

Wu, HY Wang, L Zhao, LH Wang, JL

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Publisher:: ELSEVIER
Publication Type:: Journal Article
Citation:: Neurocomputing, 2021, 457, pp. 254-264
Issue Date:: 2021-10-07

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Field	Value	Language
dc.contributor.author	Wu, HY
dc.contributor.author	Wang, L
dc.contributor.author	Zhao, LH
dc.contributor.author	Wang, JL
dc.date.accessioned	2024-03-19T03:00:10Z
dc.date.available	2024-03-19T03:00:10Z
dc.date.issued	2021-10-07
dc.identifier.citation	Neurocomputing, 2021, 457, pp. 254-264
dc.identifier.issn	0925-2312
dc.identifier.issn	1872-8286
dc.identifier.uri	http://hdl.handle.net/10453/176904
dc.description.abstract	This paper concentrates on the research of topology identification problem for coupled neural networks with multiple state couplings (CNNMSCs) or multiple delay state couplings (CNNMDSCs), in which single neural network may or may not include time delay. By constructing the response networks, designing suitable controllers and parameter adjustment schemes, utilizing several inequality techniques and significant lemmas, the topology of the original networks are identified based on synchronization between the original networks and the response networks. Finally, the validity of the proposed controllers and parameter adjustment strategies is demonstrated by two numerical examples.
dc.language	English
dc.publisher	ELSEVIER
dc.relation.ispartof	Neurocomputing
dc.relation.isbasedon	10.1016/j.neucom.2021.06.019
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	08 Information and Computing Sciences, 09 Engineering, 17 Psychology and Cognitive Sciences
dc.subject.classification	Artificial Intelligence & Image Processing
dc.subject.classification	40 Engineering
dc.subject.classification	46 Information and computing sciences
dc.subject.classification	52 Psychology
dc.title	Topology identification of coupled neural networks with multiple weights
dc.type	Journal Article
utslib.citation.volume	457
utslib.for	08 Information and Computing Sciences
utslib.for	09 Engineering
utslib.for	17 Psychology and Cognitive Sciences
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/Faculty of Engineering and Information Technology/School of Computer Science
utslib.copyright.status	closed_access	*
dc.date.updated	2024-03-19T03:00:09Z
pubs.publication-status	Published
pubs.volume	457

Abstract:

This paper concentrates on the research of topology identification problem for coupled neural networks with multiple state couplings (CNNMSCs) or multiple delay state couplings (CNNMDSCs), in which single neural network may or may not include time delay. By constructing the response networks, designing suitable controllers and parameter adjustment schemes, utilizing several inequality techniques and significant lemmas, the topology of the original networks are identified based on synchronization between the original networks and the response networks. Finally, the validity of the proposed controllers and parameter adjustment strategies is demonstrated by two numerical examples.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/176904