Adaptive Filtering Method Based on EMD

DOI

10.2991/ncce-18.2018.110How to use a DOI?

Keywords

EMD, Filtering, Adaptive denoising, IMF.

Abstract

For non-linear and non-stationary signals, traditional signal processing methods cannot effectively capture their characteristics. For this purpose, time-frequency analysis algorithms are needed to analyze the frequency domain characteristics of the signal at different times. The traditional Empirical Mode Decomposition (EMD) algorithm is a non-linear non-stationary algorithm. Its time-frequency resolution adaptively changes with the signal, so it can have higher resolution in various situations, and medical denoising and other fields have been widely used. However, when the signal-to-noise ratio is low, the performance of the EMD method is degraded due to noise. In this paper, an adaptive filtering method is proposed. By estimating the noise power under different conditions, the denoising process is adaptively performed, and a better filtering effect is achieved compared to the conventional method.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yan Rong
AU  - Shuqiang Gao
PY  - 2018/05
DA  - 2018/05
TI  - Adaptive Filtering Method Based on EMD
BT  - Proceedings of the 2018 International Conference on Network, Communication, Computer Engineering (NCCE 2018)
PB  - Atlantis Press
SP  - 671
EP  - 674
SN  - 1951-6851
UR  - https://doi.org/10.2991/ncce-18.2018.110
DO  - 10.2991/ncce-18.2018.110
ID  - Rong2018/05
ER  -