EEG Signals Denoising Using Bayesian Estimation
Jiahe Guo, Hongxv Wang, Chenjie Zhang, Xuemei Bai · 2020
Wavelet transform is a common denoising method for EEG signals, and the optimal configuration of its control parameters is the premise of improving denoising effect. In order to obtain the optimal parameters, Laplace distribution is used as the denoising model, Bayesian estimation method is used to estimate the coefficients after wavelet transform, and the estimated signals are reconstructed. Among the four groups of root-mean-square analysis data, Bayesian estimation algorithm has smaller error and better denoising effect.