@inproceedings{829af4175d0f4c95b8cae1ac77fe9ada,
title = "Algebraic Perspectives Of Background EEG Elimination",
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.",
keywords = "Average",
author = "Serap Aydin",
year = "2008",
language = "English",
series = "Biosignal-brno",
publisher = "Brno Univ Technology Vut Press",
pages = "98--100",
editor = "J Jan and J Kozumplik and I Provaznik",
booktitle = "Analysis Of Biomedical Signals And Images",
note = "19th International EURASIP Conference (BIOSIGNAL) ; Conference date: 01-06-2008",
}