Beamformer Design under Time-correlated Interference and Online Implementation: Brain-activity Reconstruction from EEG

Takehiro Kono, Masahiro Yukawa, Tomasz Piotrowski

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

1 Citation (Scopus)

Abstract

We present a convexly-constrained beamformer design for brain activity reconstruction from non-invasive electroencephalography (EEG) signals. An intrinsic gap between the output variance and the mean squared errors is highlighted that occurs due to the presence of interfering activities correlated with the desired activity. The key idea of the proposed beamformer is reducing this gap without amplifying the noise by imposing a quadratic constraint that bounds the total power of interference leakage together with the distortionless constraint. The proposed beamformer can be implemented efficiently by the multi-domain adaptive filtering algorithm. Numerical examples show the clear advantages of the proposed beamformer over the minimum-variance distortionless response (MVDR) and nulling beamformers.

Original languageEnglish
Title of host publication2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1070-1074
Number of pages5
ISBN (Electronic)9781479981311
DOIs
Publication statusPublished - 2019 May
Event44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Brighton, United Kingdom
Duration: 2019 May 122019 May 17

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume2019-May
ISSN (Print)1520-6149

Conference

Conference44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019
Country/TerritoryUnited Kingdom
CityBrighton
Period19/5/1219/5/17

Keywords

  • Electroencephalography
  • MVDR beamformer
  • inverse ploblems
  • nulling beamformer
  • relaxed zero forcing

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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