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Proceedings Paper

Sparse separation: principles and tricks
Author(s): Barak A. Pearlmutter; Vamsi K. Potluru
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Paper Abstract

Blind separation of linearly mixed white Gaussian sources is impossible, due to rotational symmetry. For this reason, all blind separation algorithms are based on some assumption concerning the fashion in which the situation departs from that insoluble case. Here we discuss the assumption of sparseness and try to put various algorithms that make the sparseness assumption in a common framework. The main objective of this paper is to give some rough intuitions, and to provide suitable hooks into the literature.

Paper Details

Date Published: 1 April 2003
PDF: 4 pages
Proc. SPIE 5102, Independent Component Analyses, Wavelets, and Neural Networks, (1 April 2003); doi: 10.1117/12.502473
Show Author Affiliations
Barak A. Pearlmutter, National Univ. of Ireland, Maynooth (Ireland)
Vamsi K. Potluru, National Univ. of Ireland, Maynooth (Ireland)

Published in SPIE Proceedings Vol. 5102:
Independent Component Analyses, Wavelets, and Neural Networks
Anthony J. Bell; Mladen V. Wickerhauser; Harold H. Szu, Editor(s)

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