Please use this identifier to cite or link to this item: https://doi.org/10.1109/LSP.2005.859526
Title: H∞ adaptive filters for eye blink artifact minimization from electroencephalogram
Authors: Puthusserypady, S. 
Ratnarajah, T.
Keywords: Blink artifacts
Electroencephalogram (EEG)
H∞ filtering
Issue Date: Dec-2005
Citation: Puthusserypady, S., Ratnarajah, T. (2005-12). H∞ adaptive filters for eye blink artifact minimization from electroencephalogram. IEEE Signal Processing Letters 12 (12) : 816-819. ScholarBank@NUS Repository. https://doi.org/10.1109/LSP.2005.859526
Abstract: Two adaptive algorithms (time varying and exponentially weighted) based on the H∞ principles are proposed for the minimization of electrooculogram (EOG) artifacts from corrupted electroencephalographic signals. Performance of the proposed algorithms are compared with the least-mean-square (LMS) algorithm. Improvements in the output signal-to-noise ratio along with time plots are used for the comparison. It is found that the H∞-based algorithms effectively minimize the EOG artifacts and always outperform the LMS algorithm. © 2005 IEEE.
Source Title: IEEE Signal Processing Letters
URI: http://scholarbank.nus.edu.sg/handle/10635/82438
ISSN: 10709908
DOI: 10.1109/LSP.2005.859526
Appears in Collections:Staff Publications

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