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• W2521172014 abstract "Electroencephalogram (EEG) reflects the physiological rhythms of brain. It has been widely used to diagnose mental disease and infer the intention of human from the Brain Computer Interface (BCI) system. Compared with other signals, it is so weak that it can be contaminated easily. In this paper, we intend to introduce a new method, orthogonal test, which is used to select the appropriate combination of mother wavelet, threshold strategy and decomposition level in wavelet transform to remove noises from EEG signal. To measure the effect of de-noising, we not only use traditional de-noising evaluate criteria, namely signal to noise ratio (SNR), root mean square error (RMSE), but also lead to a new and intuitive method, residual power spectrum (RPS), assessing the de-noising work. Correlative experimental results showing the coif3 wavelet function, Rigorous Sure threshold and 3 levels decomposition have the best performance." @default.
• W2521172014 created "2016-09-30" @default.
• W2521172014 creator A5040511249 @default.
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• W2521172014 date "2016-08-01" @default.
• W2521172014 modified "2023-09-26" @default.
• W2521172014 title "Residual power spectrum analysis in the application of EEG de-noising" @default.
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• W2521172014 doi "https://doi.org/10.1109/icma.2016.7558976" @default.
• W2521172014 hasPublicationYear "2016" @default.
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