Blind source separation based on generalised canonical correlation analysis and its adaptive realization

Wei Liu; Danilo P. Mandic; Andrzej Cichocki

doi:10.1109/CISP.2008.515

Blind source separation based on generalised canonical correlation analysis 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

7 Citations (Scopus)

Abstract

The canonical correlation analysis (CCA) approach is generalised to accommodate the case with added white noise. It is then applied to the blind source separation (BSS) problem for noisy mixtures. An adaptive blind source extraction algorithm is derived based on this idea. A proof is provided that by this generalised CCA approach, the source signals can be recovered successfully, which is also supported by simulation results.

Original language	English
Title of host publication	Proceedings - 1st International Congress on Image and Signal Processing, CISP 2008
Pages	417-421
Number of pages	5
DOIs	https://doi.org/10.1109/CISP.2008.515
Publication status	Published - Jul 2008
Event	1st International Congress on Image and Signal Processing, CISP 2008 - Sanya, Hainan, China Duration: 27 May 2008 → 30 May 2008 Conference number: 1

Publication series

Name	Proceedings - 1st International Congress on Image and Signal Processing, CISP 2008
Volume	5

Conference

Conference	1st International Congress on Image and Signal Processing, CISP 2008
Country/Territory	China
City	Sanya, Hainan
Period	27/05/08 → 30/05/08

Keywords

Blind source separation
Canonical correlation analysis
Noisy mixtures
Second-order statistics

ASJC Scopus subject areas

Computer Vision and Pattern Recognition
Signal Processing

More information

10.1109/CISP.2008.515

Cite this

Liu, W., Mandic, D. P., & Cichocki, A. (2008). Blind source separation based on generalised canonical correlation analysis and its adaptive realization. In Proceedings - 1st International Congress on Image and Signal Processing, CISP 2008 (pp. 417-421). Article 4566861 (Proceedings - 1st International Congress on Image and Signal Processing, CISP 2008; Vol. 5). https://doi.org/10.1109/CISP.2008.515

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title = "Blind source separation based on generalised canonical correlation analysis and its adaptive realization",

abstract = "The canonical correlation analysis (CCA) approach is generalised to accommodate the case with added white noise. It is then applied to the blind source separation (BSS) problem for noisy mixtures. An adaptive blind source extraction algorithm is derived based on this idea. A proof is provided that by this generalised CCA approach, the source signals can be recovered successfully, which is also supported by simulation results.",

keywords = "Blind source separation, Canonical correlation analysis, Noisy mixtures, Second-order statistics",

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Liu, W, Mandic, DP & Cichocki, A 2008, Blind source separation based on generalised canonical correlation analysis and its adaptive realization. in Proceedings - 1st International Congress on Image and Signal Processing, CISP 2008., 4566861, Proceedings - 1st International Congress on Image and Signal Processing, CISP 2008, vol. 5, pp. 417-421, 1st International Congress on Image and Signal Processing, CISP 2008, Sanya, Hainan, China, 27/05/08. https://doi.org/10.1109/CISP.2008.515

Blind source separation based on generalised canonical correlation analysis and its adaptive realization. / Liu, Wei; Mandic, Danilo P.; Cichocki, Andrzej.
Proceedings - 1st International Congress on Image and Signal Processing, CISP 2008. 2008. p. 417-421 4566861 (Proceedings - 1st International Congress on Image and Signal Processing, CISP 2008; Vol. 5).

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

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AB - The canonical correlation analysis (CCA) approach is generalised to accommodate the case with added white noise. It is then applied to the blind source separation (BSS) problem for noisy mixtures. An adaptive blind source extraction algorithm is derived based on this idea. A proof is provided that by this generalised CCA approach, the source signals can be recovered successfully, which is also supported by simulation results.

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Blind source separation based on generalised canonical correlation analysis and its adaptive realization

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

More information

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