Source identification and separation using global matrix parameters of ICA

Ganesh R. Naik, Dinesh K. Kumar, Marimuthu Palaniswami

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

11 Citations (Scopus)

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.

Original languageEnglish
Title of host publication2008 IEEE 8th International Conference on Computer and Information Technology Workshops
Place of PublicationSydney, QLD
PublisherIEEE
Pages700-705
Number of pages6
ISBN (Print)9780769533391
DOIs
Publication statusPublished - 2008
Externally publishedYes
Event8th IEEE International Conference on Computer and Information Technology Workshops, CIT Workshops 2008 - Sydney, Australia
Duration: 8 Jul 200811 Jul 2008

Publication series

NameProceedings - 8th IEEE International Conference on Computer and Information Technology Workshops, CIT Workshops 2008

Conference

Conference8th IEEE International Conference on Computer and Information Technology Workshops, CIT Workshops 2008
CountryAustralia
CitySydney
Period8/07/0811/07/08

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