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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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