Performance comparison of known ICA algorithms to a wavelet-ICA merger
Article
Walters-Williams, Janett and Li, Yan. 2011. "Performance comparison of known ICA algorithms to a wavelet-ICA merger." Signal Processing: An International Journal. 5 (3), pp. 80-92.
Article Title | Performance comparison of known ICA algorithms to a wavelet-ICA merger |
---|---|
Article Category | Article |
Authors | Walters-Williams, Janett (Author) and Li, Yan (Author) |
Journal Title | Signal Processing: An International Journal |
Journal Citation | 5 (3), pp. 80-92 |
Number of Pages | 13 |
Year | 2011 |
Web Address (URL) | http://www.cscjournals.org/csc/manuscript/Journals/SPIJ/volume5/Issue3/SPIJ-131.pdf |
Abstract | These signals are however contaminated with artifacts which must be removed to have pure EEG signals. These artifacts can be removed by Independent Component Analysis (ICA). In this paper we studied the performance of three ICA algorithms (FastICA, JADE, and Radical) as well as our newly developed ICA technique. Comparing these ICA algorithms, it is observed that our new techniques perform as well as these algorithms at denoising EEG signals. |
Keywords | independent component analysis, wavelet transform, unscented Kalman filter, electroencephalogram |
ANZSRC Field of Research 2020 | 469999. Other information and computing sciences not elsewhere classified |
400607. Signal processing | |
Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
Byline Affiliations | University of Technology, Jamaica |
Department of Mathematics and Computing | |
Institution of Origin | University of Southern Queensland |
Permalink -
https://research.usq.edu.au/item/q0z17/performance-comparison-of-known-ica-algorithms-to-a-wavelet-ica-merger
1915
total views8
total downloads1
views this month0
downloads this month