Closed-Form Estimators for Blind Separation of Sources – Part I: Real Mixtures

Authors:
Vicente Zarzoso;Asoke K. Nandi
Affiliations:
Signal Processing and Communications Group, Department of Electrical Engineering and Electronics, The University of Liverpool, Brownlow Hill, Liverpool L69 3GJ, U.K. E-mail: vicente@liverp ...;Signal Processing and Communications Group, Department of Electrical Engineering and Electronics, The University of Liverpool, Brownlow Hill, Liverpool L69 3GJ, U.K.
Venue:
Wireless Personal Communications: An International Journal
Year:
2002

Citing 10
Cited 2

Independent component analysis, a new concept?

Signal Processing - Special issue on higher order statistics
Maximum likelihood estimators and Cramer-Rao bounds in source separation

Signal Processing
Time series: data analysis and theory

Time series: data analysis and theory
Multiuser Detection

Multiuser Detection
Wideband CDMA For Third Generation Mobile Communications: Universal Personal Communications

Wideband CDMA For Third Generation Mobile Communications: Universal Personal Communications
Blind separation of linear instantaneous mixtures using closed-form estimators

Signal Processing
Closed-Form Estimators for Blind Separation of Sources – Part II: Complex Mixtures

Wireless Personal Communications: An International Journal
Blind source separation without optimization criteria?

ICASSP '99 Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 03
Blind separation of independent sources for virtually any sourceprobability density function

IEEE Transactions on Signal Processing
Adaptive blind source separation for virtually any sourceprobability density function

IEEE Transactions on Signal Processing

Closed-Form Estimators for Blind Separation of Sources – Part II: Complex Mixtures

Wireless Personal Communications: An International Journal
ICA by PCA approach: relating higher-order statistics to second-order moments

ICA'06 Proceedings of the 6th international conference on Independent Component Analysis and Blind Signal Separation

Quantified Score

Hi-index	0.00

Visualization

Abstract

The problem of multiuser interference cancellation in wireless cellularcommunication systems accepts a blind source separation (BSS) model. Thepresent contribution studies the closed-form solutions to BSS in thereal-mixture case. Connections among a number of seemingly disparate methodsare unveiled, new procedures are put forward, and their asymptotic(large-sample) performance is analyzed. Simulation experiments illustrate andvalidate the theoretical results. Altogether, a unifying generic framework forclosed-form BSS methods is developed.