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

Authors

Guoqiang Yan, College of Computer, Nanjing University of Posts and Telecommunications, Nanjing 210000, China;
Ningning Zhou, College of Computer, Nanjing University of Posts and Telecommunications, Nanjing 210000, China;
Shaobai Zhang, College of Computer, Nanjing University of Posts and Telecommunications, Nanjing 210000, China;

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.

Recommended Citation

Yan, Guoqiang; Zhou, Ningning; and Zhang, Shaobai (2019) "De-noising Method of EEG Signal Based on MMTD and Wavelet Hard-threshold," Journal of System Simulation: Vol. 30: Iss. 4, Article 34.
DOI: 10.16182/j.issn1004731x.joss.201804034
Available at: https://dc-china-simulation.researchcommons.org/journal/vol30/iss4/34

First Page

1490

Revised Date

2016-07-06

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.201804034

Last Page

1495

CLC

TP391.9

Recommended Citation

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.

DOI

10.16182/j.issn1004731x.joss.201804034