On real and complex valued ℓ 1-norm minimization for overcomplete blind source separation

Stefan Winter*, Hiroshi Sawada, Shoji Makino

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

34 Citations (Scopus)

Abstract

A maximum a-posteriori approach for overcomplete blind source separation based on Laplacian priors usually involves ℓ 1 -norm minimization. It requires different approaches for real and complex numbers as they appear for example in the frequency domain. In this paper we compare a combinatorial approach for real numbers with a second order cone programming approach for complex numbers. Although the combinatorial solution with a proven minimum number of zeros is not theoretically justified for complex numbers, its performance quality is comparable to the performance of the second order cone programming (SOCP) solution. However, it has the advantage that it is faster for complex overcomplete BSS problems with low input/output dimensions.

Original languageEnglish
Title of host publication2005 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics
Pages86-89
Number of pages4
DOIs
Publication statusPublished - 2005
Externally publishedYes
Event2005 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics - New Paltz, NY, United States
Duration: 2005 Oct 162005 Oct 19

Publication series

NameIEEE Workshop on Applications of Signal Processing to Audio and Acoustics

Conference

Conference2005 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics
Country/TerritoryUnited States
CityNew Paltz, NY
Period05/10/1605/10/19

ASJC Scopus subject areas

  • Signal Processing

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