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Double density wavelet for EEG signal denoising

Abdullah, Haslaile and Cvetkovic, Dean. (2013) Double density wavelet for EEG signal denoising. In: 2nd International Conference on Machine Learning and Computer Science, 2013.

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EEG signals usually were contaminated with unwanted artefacts that may hide some valuable information in the signals. In this paper, we implemented wavelet based image processing techniques known as 1-D Double Density and 1-D Double Density Complex for denoising EEG signals at various windows size. The performances of these methods were compared and evaluated by calculating the Root Mean Square Error (RMSE). The minimum RMSE was achieved at the threshold value of 20. The 1-D Double Density Complex was outperformed 1-D Double Density and was effective in EEG signals denoising.

Item Type:Conference or Workshop Item (Paper)
Subjects:T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:Razak School of Engineering and Advanced Technology
ID Code:37573
Deposited By: Liza Porijo
Deposited On:14 Apr 2014 04:37
Last Modified:25 Sep 2017 08:30

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