A class of novel blind source extraction algorithms based on a linear predictor

A rigorous analysis of the performance of a blind source extraction structure based on a linear predictor is provided. It is shown that by minimising the mean square prediction error, it is only possible to reach a solution subject to an arbitrary orthogonal transformation, in a manner similar to th...

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Bibliographic Details
Published in2005 IEEE International Symposium on Circuits and Systems (ISCAS) pp. 3599 - 3602 Vol. 4
Main Authors Wei Liu, Mandic, D.P., Cichocki, A.
Format Conference Proceeding
LanguageEnglish
Published IEEE 2005
Subjects
Algorithm design and analysis
Educational institutions
Higher order statistics
Laboratories
Performance analysis
Principal component analysis
Signal analysis
Signal processing algorithms
Uncertainty
Vectors
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ISBN9780780388345
0780388348
ISSN0271-4302
DOI10.1109/ISCAS.2005.1465408

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Summary:A rigorous analysis of the performance of a blind source extraction structure based on a linear predictor is provided. It is shown that by minimising the mean square prediction error, it is only possible to reach a solution subject to an arbitrary orthogonal transformation, in a manner similar to the principal component analysis. To remove this uncertainty, we propose a new cost function which caters for the ambiguous power levels of the source signals. A novel adaptive blind source extraction algorithm is derived and an alternative method with prewhitening is also introduced. Simulation results verify the proposed algorithms.
ISBN:9780780388345
0780388348
ISSN:0271-4302
DOI:10.1109/ISCAS.2005.1465408