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In this paper, we propose a new denoise method for noisy electrocardiogram (ECG) signals. We employ an n-gram-based wavelet learning in order to investigate optimal classical wavelet sequences for ECG signals denoise. Our main approach separates the ECG signal of the interest into multi-windows then assigns the optimal wavelet to each window. The wavelet learning approach uses the mean square error(MSE)...
In brain signals analysis, there are the supplementary devices such as EEG, fNIRS, MEG, fMRI, PET, etc. EEG is a popular secondary device due to the advantages of easy usability, mobility and low-cost. Many researchers have employed a Discrete Wavelet Transform (DWT) to classify EEG signals and make a clustering of the signal in brain-computer interface and medicine diagnosis. The precision of classification...
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