Conference Publication Details
Mandatory Fields
Pearlmutter, BA;Potluru, VK
INDEPENDENT COMPONENT ANALYSES, WAVELETS, AND NEURAL NETWORKS
Sparse separation: Principles and tricks
2003
January
Published
1
9 ()
Optional Fields
BLIND SOURCE SEPARATION
1
4
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.
Grant Details