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Recursive Complex Blind Source Separation via Eigendecomposition of Cumulant Matrices

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4 Author(s)
Puskal P. Pokharel ; Computational NeuroEnginering Laboratory, ECE Department, University of Florida ; Umut Ozertem ; Deniz Erdogmus ; Jose C. Principe

Under the assumptions of non-Gaussian, non-stationary, or non-white independent sources, linear blind source separation can be formulated as a generalized eigenvalue decomposition problem. Here we provide an elegant method of doing this online, instead of waiting for a sufficiently large batch of data. This is done through a recursive generalized eigendecomposition algorithm that tracks the optimal solution, which is obtained using all the data observed. The algorithms proposed in this paper follow the well-known recursive least squares (RLS) algorithm in nature.

Published in:

2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07  (Volume:2 )

Date of Conference:

15-20 April 2007