Source identification and separation using global matrix parameters of ICA

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

doi:10.1109/CIT.2008.Workshops.58

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 proceeding › Conference contribution › peer-review

14 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 language	English
Title of host publication	2008 IEEE 8th International Conference on Computer and Information Technology Workshops
Place of Publication	Sydney, QLD
Publisher	IEEE
Pages	700-705
Number of pages	6
ISBN (Print)	9780769533391
DOIs	https://doi.org/10.1109/CIT.2008.Workshops.58
Publication status	Published - 2008
Externally published	Yes
Event	8th IEEE International Conference on Computer and Information Technology Workshops, CIT Workshops 2008 - Sydney, Australia Duration: 8 Jul 2008 → 11 Jul 2008

Publication series

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

Conference

Conference	8th IEEE International Conference on Computer and Information Technology Workshops, CIT Workshops 2008
Country	Australia
City	Sydney
Period	8/07/08 → 11/07/08

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Naik, G. R., Kumar, D. K., & Palaniswami, M. (2008). Source identification and separation using global matrix parameters of ICA. In 2008 IEEE 8th International Conference on Computer and Information Technology Workshops (pp. 700-705). [4568586] (Proceedings - 8th IEEE International Conference on Computer and Information Technology Workshops, CIT Workshops 2008). IEEE. https://doi.org/10.1109/CIT.2008.Workshops.58

Naik, Ganesh R. ; Kumar, Dinesh K. ; Palaniswami, Marimuthu. / Source identification and separation using global matrix parameters of ICA. 2008 IEEE 8th International Conference on Computer and Information Technology Workshops. Sydney, QLD : IEEE, 2008. pp. 700-705 (Proceedings - 8th IEEE International Conference on Computer and Information Technology Workshops, CIT Workshops 2008).

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title = "Source identification and separation using global matrix parameters of ICA",

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.",

author = "Naik, {Ganesh R.} and Kumar, {Dinesh K.} and Marimuthu Palaniswami",

year = "2008",

doi = "10.1109/CIT.2008.Workshops.58",

language = "English",

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series = "Proceedings - 8th IEEE International Conference on Computer and Information Technology Workshops, CIT Workshops 2008",

publisher = "IEEE",

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Naik, GR, Kumar, DK & Palaniswami, M 2008, Source identification and separation using global matrix parameters of ICA. in 2008 IEEE 8th International Conference on Computer and Information Technology Workshops., 4568586, Proceedings - 8th IEEE International Conference on Computer and Information Technology Workshops, CIT Workshops 2008, IEEE, Sydney, QLD, pp. 700-705, 8th IEEE International Conference on Computer and Information Technology Workshops, CIT Workshops 2008, Sydney, Australia, 8/07/08. https://doi.org/10.1109/CIT.2008.Workshops.58

Source identification and separation using global matrix parameters of ICA. / Naik, Ganesh R.; Kumar, Dinesh K.; Palaniswami, Marimuthu.

2008 IEEE 8th International Conference on Computer and Information Technology Workshops. Sydney, QLD : IEEE, 2008. p. 700-705 4568586 (Proceedings - 8th IEEE International Conference on Computer and Information Technology Workshops, CIT Workshops 2008).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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N2 - 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.

AB - 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.

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Naik GR, Kumar DK, Palaniswami M. Source identification and separation using global matrix parameters of ICA. In 2008 IEEE 8th International Conference on Computer and Information Technology Workshops. Sydney, QLD: IEEE. 2008. p. 700-705. 4568586. (Proceedings - 8th IEEE International Conference on Computer and Information Technology Workshops, CIT Workshops 2008). https://doi.org/10.1109/CIT.2008.Workshops.58

Source identification and separation using global matrix parameters of ICA

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