A two-stage MMSE beamformer for underdetermined signal separation

Zbyněk Koldovský, Petr Tichavský, Anh Huy Phan, Andrzej Cichocki

Research output: Contribution to journalArticlepeer-review

17 Citations (Scopus)

Abstract

Blind separation of underdetermined instantaneous mixtures is a popular solution to inverse problems encountered in audio or biomedical applications where the number of sources exceeds the number of sensors. There are two non-equivalent tasks: to identify the mixing matrix and to separate the original sources. In this paper, we focus on the latter task by proposing a novel beamformer that minimizes the theoretical mean square error distance between the separated and original signals. The beamformer has two stages: one for the estimation of signals and one for their refinement. Within the former stage, the signals are assumed to be random and locally stationary, while the latter stage is based on a semi-deterministic model. The experiments prove superior performance of the proposed method compared to conventional MMSE beamforming.

Original languageEnglish
Article number6634221
Pages (from-to)1227-1230
Number of pages4
JournalIEEE Signal Processing Letters
Volume20
Issue number12
DOIs
Publication statusPublished - 2013
Externally publishedYes

Keywords

  • Beamforming
  • blind source separation
  • nonstationary processes
  • underdetermined mixtures

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