Complete Blind Subspace Deconvolution

Authors:
Zoltán Szabó
Affiliations:
Department of Information Systems, Eötvös Loránd University, Budapest, Hungary H-1117
Venue:
ICA '09 Proceedings of the 8th International Conference on Independent Component Analysis and Signal Separation
Year:
2009

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Abstract

In this paper we address the blind subspace deconvolution (BSSD) problem; an extension of both the blind source deconvolution (BSD) and the independent subspace analysis (ISA) tasks. While previous works have been focused on the undercomplete case, here we extend the theory to complete systems. Particularly, we derive a separation technique for the complete BSSD problem: we solve the problem by reducing the estimation task to ISA via linear prediction. Numerical examples illustrate the efficiency of the proposed method.