De-noising Method of EEG Signal Based on MMTD and Wavelet Hard-threshold

doi:10.16182/j.issn1004731x.joss.201804034

Abstract

Abstract: To overcome the shortage of losing partial important information of hard-threshold method with EEG signal de-noising process, a novel de-noising method based on the combination of measuring of medium truth degree (MMTD) and EEG is proposed. By decomposing noisy signals of wavelet transform, handling threshold of high-frequency wavelet coefficients in every layer, and reconstructing post-processing of the wavelet coefficients, the purpose of noise elimination can be guaranteed. Under different noise intensity, the experimental results show that the MAWH (MMTD and wavelet hard-threshold) method has perspective of lower RMSE and higher SNR compared to hard-threshold and soft-threshold.

Key words: electroencephalograph, de-noising, hard-threshold, MMTD, wavelet transform

CLC Number:

TP391.9

Yan Guoqiang, Zhou Ningning, Zhang Shaobai. De-noising Method of EEG Signal Based on MMTD and Wavelet Hard-threshold[J]. Journal of System Simulation, 2018, 30(4): 1490-1495.

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