A new approach to denoising EEG signals - merger of translation invariant wavelet and ICA
Article
Article Title | A new approach to denoising EEG signals - merger of translation invariant wavelet and ICA |
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ERA Journal ID | 125247 |
Article Category | Article |
Authors | Walters-Williams, Janett (Author) and Li, Yan (Author) |
Journal Title | International Journal of Biometrics and Bioinformatics (IJBB) |
Journal Citation | 5 (2), pp. 130-148 |
Number of Pages | 19 |
Year | 2011 |
Place of Publication | Kuala Lumpur, Malaysia |
ISSN | 1985-2347 |
Web Address (URL) | http://www.cscjournals.org/manuscript/Journals/IJBB/volume5/Issue2/IJBB-65.pdf |
Abstract | In this paper we present a new algorithm using a merger of Independent Component Analysis and Translation Invariant Wavelet Transform. The efficacy of this algorithm is evaluated by applying contaminated EEG signals. Its performance was compared to three fixed-point ICA algorithms (FastICA, EFICA and Pearson-ICA) using Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR), Signal to Distortion Ratio (SDR), and Amari Performance Index. |
Keywords | independent component analysis; wavelet transform; unscented Kalman filter; electroencephalogram (EEG); cycle spinning |
ANZSRC Field of Research 2020 | 469999. Other information and computing sciences not elsewhere classified |
400607. Signal processing | |
320602. Medical biotechnology diagnostics (incl. biosensors) | |
310104. Cell neurochemistry | |
Public Notes | Copyright 2011 Computer Science Journals. Open access journal. This publication is copyright. It may be reproduced in whole or in part for the purposes of study, research, or review, but is subject to the inclusion of an acknowledgment of the source. |
Byline Affiliations | University of Technology, Jamaica |
Department of Mathematics and Computing | |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q0z21/a-new-approach-to-denoising-eeg-signals-merger-of-translation-invariant-wavelet-and-ica
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