An analysis of the CCA approach for blind source separation and its adaptive realization

Wei Liu; Danilo P. Mandic; Andrzej Cichocki

An analysis of the CCA approach for blind source separation and its adaptive realization

Wei Liu, Danilo P. Mandic, Andrzej Cichocki

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

Abstract

An analysis of the canonical correlation analysis (CCA) approach in blind source separation is provided. In particular, it is proved that by maximizing the autocorrelation functions of the recovered signals we can separate the source signals successfully. We show that the CCA approach represents the same generalised eigenvalue decomposition problem introduced in the matrix pencil method. Finally, an adaptive blind source extraction (BSE) algorithm is derived as an online realisation of the CCA approach. Simulation results verify the proposed approach.

Original language	English
Title of host publication	ISCAS 2006
Subtitle of host publication	2006 IEEE International Symposium on Circuits and Systems, Proceedings
Pages	3590-3593
Number of pages	4
Publication status	Published - May 2006
Event	ISCAS 2006: 2006 IEEE International Symposium on Circuits and Systems - Kos, Greece Duration: 21 May 2006 → 24 May 2006

Publication series

Name	Proceedings - IEEE International Symposium on Circuits and Systems
ISSN (Print)	0271-4310

Conference

Conference	ISCAS 2006: 2006 IEEE International Symposium on Circuits and Systems
Country/Territory	Greece
City	Kos
Period	21/05/06 → 24/05/06

ASJC Scopus subject areas

Electrical and Electronic Engineering

Cite this

@inproceedings{a75045bf81b843f6884e7dd81fbdc8cb,

title = "An analysis of the CCA approach for blind source separation and its adaptive realization",

abstract = "An analysis of the canonical correlation analysis (CCA) approach in blind source separation is provided. In particular, it is proved that by maximizing the autocorrelation functions of the recovered signals we can separate the source signals successfully. We show that the CCA approach represents the same generalised eigenvalue decomposition problem introduced in the matrix pencil method. Finally, an adaptive blind source extraction (BSE) algorithm is derived as an online realisation of the CCA approach. Simulation results verify the proposed approach.",

author = "Wei Liu and Mandic, {Danilo P.} and Andrzej Cichocki",

year = "2006",

month = may,

language = "English",

isbn = "0780393902",

series = "Proceedings - IEEE International Symposium on Circuits and Systems",

pages = "3590--3593",

booktitle = "ISCAS 2006",

note = "ISCAS 2006: 2006 IEEE International Symposium on Circuits and Systems ; Conference date: 21-05-2006 Through 24-05-2006",

}

Liu, W, Mandic, DP & Cichocki, A 2006, An analysis of the CCA approach for blind source separation and its adaptive realization. in ISCAS 2006: 2006 IEEE International Symposium on Circuits and Systems, Proceedings., 1693403, Proceedings - IEEE International Symposium on Circuits and Systems, pp. 3590-3593, ISCAS 2006: 2006 IEEE International Symposium on Circuits and Systems, Kos, Greece, 21/05/06.

An analysis of the CCA approach for blind source separation and its adaptive realization. / Liu, Wei; Mandic, Danilo P.; Cichocki, Andrzej.
ISCAS 2006: 2006 IEEE International Symposium on Circuits and Systems, Proceedings. 2006. p. 3590-3593 1693403 (Proceedings - IEEE International Symposium on Circuits and Systems).

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

TY - GEN

T1 - An analysis of the CCA approach for blind source separation and its adaptive realization

AU - Liu, Wei

AU - Mandic, Danilo P.

AU - Cichocki, Andrzej

PY - 2006/5

Y1 - 2006/5

N2 - An analysis of the canonical correlation analysis (CCA) approach in blind source separation is provided. In particular, it is proved that by maximizing the autocorrelation functions of the recovered signals we can separate the source signals successfully. We show that the CCA approach represents the same generalised eigenvalue decomposition problem introduced in the matrix pencil method. Finally, an adaptive blind source extraction (BSE) algorithm is derived as an online realisation of the CCA approach. Simulation results verify the proposed approach.

AB - An analysis of the canonical correlation analysis (CCA) approach in blind source separation is provided. In particular, it is proved that by maximizing the autocorrelation functions of the recovered signals we can separate the source signals successfully. We show that the CCA approach represents the same generalised eigenvalue decomposition problem introduced in the matrix pencil method. Finally, an adaptive blind source extraction (BSE) algorithm is derived as an online realisation of the CCA approach. Simulation results verify the proposed approach.

UR - http://www.scopus.com/inward/record.url?scp=34547285002&partnerID=8YFLogxK

M3 - Conference article published in proceeding or book

AN - SCOPUS:34547285002

SN - 0780393902

SN - 9780780393905

T3 - Proceedings - IEEE International Symposium on Circuits and Systems

SP - 3590

EP - 3593

BT - ISCAS 2006

T2 - ISCAS 2006: 2006 IEEE International Symposium on Circuits and Systems

Y2 - 21 May 2006 through 24 May 2006

ER -

An analysis of the CCA approach for blind source separation and its adaptive realization

Abstract

Publication series

Conference

ASJC Scopus subject areas

Other files and links

Fingerprint

Cite this