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

Western Sydney University

Research output: Chapter in Book / Conference Paper › Conference Paper › peer-review

17 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	Proceedings 8th IEEE International Conference on Computer and Information Technology Workshops, CIT Workshops 2008, Sydney, N.S.W., 8-11 July 2008
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
Event	IEEE International Conference on Computer and Information Technology. Workshops - Duration: 8 Jul 2008 → …

Conference

Conference	IEEE International Conference on Computer and Information Technology. Workshops
Period	8/07/08 → …

Keywords

blind source separation
independent component analysis
matrices
parameter estimation
signal processing

Access to Document

10.1109/CIT.2008.Workshops.58

Cite this

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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.",

keywords = "blind source separation, independent component analysis, matrices, parameter estimation, signal processing",

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

year = "2008",

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

language = "English",

isbn = "9780769533391",

pages = "700--705",

booktitle = "Proceedings 8th IEEE International Conference on Computer and Information Technology Workshops, CIT Workshops 2008, Sydney, N.S.W., 8-11 July 2008",

publisher = "IEEE",

note = "IEEE International Conference on Computer and Information Technology. Workshops ; Conference date: 08-07-2008",

}

Naik, GR, Kumar, DK & Palaniswami, M 2008, Source identification and separation using global matrix parameters of ICA. in Proceedings 8th IEEE International Conference on Computer and Information Technology Workshops, CIT Workshops 2008, Sydney, N.S.W., 8-11 July 2008. IEEE, pp. 700-705, IEEE International Conference on Computer and Information Technology. Workshops, 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.
Proceedings 8th IEEE International Conference on Computer and Information Technology Workshops, CIT Workshops 2008, Sydney, N.S.W., 8-11 July 2008. IEEE, 2008. p. 700-705.

Research output: Chapter in Book / Conference Paper › Conference Paper › peer-review

TY - GEN

T1 - Source identification and separation using global matrix parameters of ICA

AU - Naik, Ganesh R.

AU - Kumar, Dinesh K.

AU - Palaniswami, Marimuthu

PY - 2008

Y1 - 2008

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.

KW - blind source separation

KW - independent component analysis

KW - matrices

KW - parameter estimation

KW - signal processing

UR - http://handle.westernsydney.edu.au:8081/1959.7/uws:43756

U2 - 10.1109/CIT.2008.Workshops.58

DO - 10.1109/CIT.2008.Workshops.58

M3 - Conference Paper

SN - 9780769533391

SP - 700

EP - 705

BT - Proceedings 8th IEEE International Conference on Computer and Information Technology Workshops, CIT Workshops 2008, Sydney, N.S.W., 8-11 July 2008

PB - IEEE

T2 - IEEE International Conference on Computer and Information Technology. Workshops

Y2 - 8 July 2008

ER -

Source identification and separation using global matrix parameters of ICA

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Keywords

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