Blind separation of convolved mixtures in the frequency domain

Research output: Contribution to journalArticlepeer-review

Abstract

In this paper we employ information theoretic algorithms, previously used for separating instantaneous mixtures of sources, for separating convolved mixing in the frequency domain. It is observed that convolved mixing in the time domain corresponds to instantaneous mixing in the frequency domain. Such mixing can be inverted using simpler and more robust algorithms than the ones recently developed. Advantages of this approach are improved efficiency and better convergence features.

Original languageEnglish (US)
Pages (from-to)21-34
Number of pages14
JournalNeurocomputing
Volume22
Issue number1-3
DOIs
StatePublished - Nov 20 1998
Externally publishedYes

Keywords

  • Convolved mixtures
  • Frequency domain
  • Information theoretic algorithms
  • Separation

ASJC Scopus subject areas

  • Computer Science Applications
  • Cognitive Neuroscience
  • Artificial Intelligence

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