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|Title:||H∞ adaptive filters for eye blink artifact minimization from electroencephalogram||Authors:||Puthusserypady, S.
|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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