Source identification and separation using global matrix parameters of ICA

Naik, GR; Kumar, DK; Palaniswami, M

Source identification and separation using global matrix parameters of ICA

Naik, GR

Kumar, DK Palaniswami, M

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Publication Type:: Conference Proceeding
Citation:: Proceedings - 8th IEEE International Conference on Computer and Information Technology Workshops, CIT Workshops 2008, 2008, pp. 700 - 705
Issue Date:: 2008-09-24

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Field	Value	Language
dc.contributor.author	Naik, GR https://orcid.org/0000-0003-1790-9838	en_US
dc.contributor.author	Kumar, DK	en_US
dc.contributor.author	Palaniswami, M	en_US
dc.date.issued	2008-09-24	en_US
dc.identifier.citation	Proceedings - 8th IEEE International Conference on Computer and Information Technology Workshops, CIT Workshops 2008, 2008, pp. 700 - 705	en_US
dc.identifier.isbn	9780769533391	en_US
dc.identifier.uri	http://hdl.handle.net/10453/26722
dc.description.abstract	Successful separation of independent sources using Blind Source Separation (BSS) techniques requires estimating the number of independent sources in the mixture. Independent component analysis (ICA) is on of the widely used BSS techniques for source separation and identification in audio and bio signal processing. This paper has proposed the use of determinant of the global matrix of ICA as a measure of the number of independent and dependent sources in a mixture of signals. The paper reports experimental verification of the proposed technique where the values of the determinant are seen to be closely based on the number of dependent sources in the mixture. © 2008 IEEE. DOI 10.1109/CIT.2008.Workshops.58.	en_US
dc.relation.ispartof	Proceedings - 8th IEEE International Conference on Computer and Information Technology Workshops, CIT Workshops 2008	en_US
dc.relation.isbasedon	10.1109/CIT.2008.Workshops.58	en_US
dc.title	Source identification and separation using global matrix parameters of ICA	en_US
dc.type	Conference Proceeding
utslib.for	090609 Signal Processing	en_US
utslib.for	090302 Biomechanical Engineering	en_US
utslib.for	090399 Biomedical Engineering not elsewhere classified	en_US
dc.location.activity	Sydney	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

Successful separation of independent sources using Blind Source Separation (BSS) techniques requires estimating the number of independent sources in the mixture. Independent component analysis (ICA) is on of the widely used BSS techniques for source separation and identification in audio and bio signal processing. This paper has proposed the use of determinant of the global matrix of ICA as a measure of the number of independent and dependent sources in a mixture of signals. The paper reports experimental verification of the proposed technique where the values of the determinant are seen to be closely based on the number of dependent sources in the mixture. © 2008 IEEE. DOI 10.1109/CIT.2008.Workshops.58.

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http://hdl.handle.net/10453/26722