Peer-Reviewed Journal Details
Mandatory Fields
O'Grady, PD;Pearlmutter, BA
2008
January
Eurasip Journal on Advances in Signal Processing
The LOST Algorithm: Finding Lines and Separating Speech Mixtures
Published
20 ()
Optional Fields
BLIND SOURCE SEPARATION INDEPENDENT COMPONENT ANALYSIS SPARSE
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 L(1)-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.
NEW YORK
1687-6172
10.1155/2008/784296
Grant Details