O'Grady, Paul D. and Pearlmutter, Barak A. (2008) The LOST Algorithm: finding lines and separating speech mixtures. EURASIP Journal on Advances in Signal Processing . pp. 1-17. ISSN 1687-6172

Download (6MB)

Abstract

Robust clustering of data into linear subspaces is a frequently encountered problem. Here, we treat clustering of one-dimensional subspaces that cross the origin. This problem arises in blind source separation, where the subspaces correspond directly to columns of a mixing matrix. We propose the LOST algorithm, which identifies such subspaces using a procedure similar in spirit to EM. This line finding procedure combined with a transformation into a sparse domain and an L1-norm minimisation constitutes a blind source separation algorithm for the separation of instantaneous mixtures with an arbitrary number of mixtures and sources. We perform an extensive investigation on the general separation performance of the LOST algorithm using randomly generated mixtures, and empirically estimate the performance of the algorithm in the presence of noise. Furthermore, we implement a simple scheme whereby the number of sources present in the mixtures can be detected automatically

Item Type:	Article
Additional Information:	All articles published in Hindawi journals are open access and distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Keywords:	Blind source separation (BSS); Sparseness assumption; LOST algorithm; Separating Speech mixtures; Hamilton Institute;
Academic Unit:	Faculty of Science and Engineering > Computer Science Faculty of Science and Engineering > Research Institutes > Hamilton Institute
Item ID:	1699
Identification Number:	https://doi.org/10.1155/2008/784296
Depositing User:	Hamilton Editor
Date Deposited:	01 Dec 2009 12:45
Journal or Publication Title:	EURASIP Journal on Advances in Signal Processing
Publisher:	Hindawi Publishing Corporation
Refereed:	Yes
URI:	Publisher
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

Repository Staff Only(login required)

Item control page

Downloads

Origin of downloads