Equivalence between Frequency-Domain Blind Source Separation and Frequency-Domain Adaptive Beamforming for Convolutive Mixtures

Shoko Araki*, Shoji Makino, Yoichi Hinamoto, Ryo Mukai, Tsuyoki Nishikawa, Hiroshi Saruwatari

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

70 Citations (Scopus)

Abstract

Frequency-domain blind source separation (ESS) is shown to be equivalent to two sets of frequency-domain adaptive beamformers (ABFs) under certain conditions. The zero search of the off-diagonal components in the BSS update equation can be viewed as the minimization of the mean square error in the ABFs. The unmixing matrix of the BSS and the filter coefficients of the ABFs converge to the same solution if the two source signals are ideally independent. If they are dependent, this results in a bias for the correct unmixing filter coefficients. Therefore, the performance of the BSS is limited to that of the ABF if the ABF can use exact geometric information. This understanding gives an interpretation of BSS from a physical point of view.

Original languageEnglish
Pages (from-to)1157-1166
Number of pages10
JournalEurasip Journal on Applied Signal Processing
Volume2003
Issue number11
DOIs
Publication statusPublished - 2003 Oct 1
Externally publishedYes

Keywords

  • Adaptive beamformers
  • Blind source separation
  • Convolutive mixtures

ASJC Scopus subject areas

  • Signal Processing
  • Hardware and Architecture
  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'Equivalence between Frequency-Domain Blind Source Separation and Frequency-Domain Adaptive Beamforming for Convolutive Mixtures'. Together they form a unique fingerprint.

Cite this