ICA 2007

ICA 2007
7th International Conference on
Independent Component Analysis
and Signal Separation

London, UK        9 - 12 September 2007

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Paper No: 111

Linear Prediction Based Blind Source Extraction Algorithms in Practical Applications

Author(s): Zhi-Lin Zhang, Liqing Zhang


Blind source extraction (BSE) is of advantages over blind source separation (BSS) when obtaining some underlying source signals from high dimensional observed signals. Among a variety of BSE algorithms, a large class is the one based on linear prediction (LP-BSE). In this paper we analyze practical implementation issues of the algorithms. We reveal that they are, in nature, the minor component analysis (MCA) algorithms, and thus they have some problems that are inherent in the MCA algorithms. We also find a switch phenomena of online LP-BSE algorithms, which means that different parts of a single extracted signal are the counterparts of different source signals. The two issues should be noticed when one applies these algorithms to practical applications. Computer simulations are given to confirm the results.

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