Algebraic Perspectives Of Background EEG Elimination

AYDIN S.

19th International EURASIP Conference (BIOSIGNAL), Brno, Czech Republic, 01 June 2008, pp.98-100 identifier

  • Publication Type: Conference Paper / Full Text
  • City: Brno
  • Country: Czech Republic
  • Page Numbers: pp.98-100
  • Ondokuz Mayıs University Affiliated: No

Abstract

Least squares linear mapping (LSLM) algorithm is applied to reduce the background EEG noise on single-trial auditory evoked potentials (EPs) in the present study. Relationships between eigenvalues and spectral signal-to-noise ratio (SNR) are shown where a small number of noisy sweeps are considered as a raw matrix corrupted with additive noise. Results show that the LSLM can be assigned as a pre-filter in single trial EP estimations. Dominant eigenvectors of noisy EPs models the noiseless EP waveforms.