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Please use this identifier to cite or link to this item: https://doi.org/10.1109/LSP.2005.859526
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dc.titleH∞ adaptive filters for eye blink artifact minimization from electroencephalogram
dc.contributor.authorPuthusserypady, S.
dc.contributor.authorRatnarajah, T.
dc.date.accessioned2014-10-07T04:29:24Z
dc.date.available2014-10-07T04:29:24Z
dc.date.issued2005-12
dc.identifier.citationPuthusserypady, 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
dc.identifier.issn10709908
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/82438
dc.description.abstractTwo 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.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1109/LSP.2005.859526
dc.sourceScopus
dc.subjectBlink artifacts
dc.subjectElectroencephalogram (EEG)
dc.subjectH∞ filtering
dc.typeArticle
dc.contributor.departmentELECTRICAL & COMPUTER ENGINEERING
dc.description.doi10.1109/LSP.2005.859526
dc.description.sourcetitleIEEE Signal Processing Letters
dc.description.volume12
dc.description.issue12
dc.description.page816-819
dc.description.codenISPLE
dc.identifier.isiut000233811600004
Appears in Collections:Staff Publications

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