Blind signal separation: statistical principles
- 1 October 1998
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in Proceedings of the IEEE
- Vol. 86 (10) , 2009-2025
- https://doi.org/10.1109/5.720250
Abstract
Blind signal separation (BSS) and independent component analysis (ICA) are emerging techniques of array processing and data analysis that aim to recover unobserved signals or "sources" from observed mixtures (typically, the output of an array of sensors), exploiting only the assumption of mutual independence between the signals. The weakness of the assumptions makes it a powerful approach, but it requires us to venture beyond familiar second order statistics, The objectives of this paper are to review some of the approaches that have been developed to address this problem, to illustrate how they stem from basic principles, and to show how they relate to each other.Keywords
This publication has 50 references indexed in Scilit:
- An unconstrained single stage criterion for blind source separationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Independent component analysis based on higher-order statistics onlyPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- An extended fourth order blind identification algorithm in spatially correlated noisePublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Some experiments with array data collected in actual urban and suburban environmentsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Fetal electrocardiogram extraction by blind source subspace separationIEEE Transactions on Biomedical Engineering, 2000
- Blind separation of mixture of independent sources through a quasi-maximum likelihood approachIEEE Transactions on Signal Processing, 1997
- A unified stability analysis of the Hérault-Jutten source separation neural networkSignal Processing, 1996
- Asymptotic performance analysis of blind signal copy using fourth-order cumulantsInternational Journal of Adaptive Control and Signal Processing, 1996
- Adaptive blind separation of independent sources: A deflation approachSignal Processing, 1995
- ON MINIMUM ENTROPY DECONVOLUTIONPublished by Elsevier ,1981