JOURNAL ARTICLE

Random Noise Reduction Based on Ensemble Empirical Mode Decomposition and Wavelet Threshold Filtering

Wei ChenShang Xu WangXiao Yu ChuaiZhen Zhang

Year: 2012 Journal:   Advanced materials research Vol: 518-523 Pages: 3887-3890   Publisher: Trans Tech Publications

Abstract

This paper presents a random noise reduction method based on ensemble empirical mode decomposition (EEMD) and wavelet threshold filtering. Firstly, we have conducted spectrum analysis and analyzed the frequency band range of effective signals and noise. Secondly, we make use of EEMD method on seismic signals to obtain intrinsic mode functions (IMFs) of each trace. Then, wavelet threshold noise reduction method is used on the high frequency IMFs of each trace to obtain new high frequency IMFs. Finally, reconstruct the desired signal by adding the new high frequency IMFs on the low frequency IMFs and the trend item together. When applying our method on synthetic seismic record and field data we can get good results.

Keywords:
Hilbert–Huang transform Noise reduction Wavelet Noise (video) Computer science Artificial intelligence Reduction (mathematics) Pattern recognition (psychology) Range (aeronautics) Mode (computer interface) SIGNAL (programming language) Algorithm Speech recognition Filter (signal processing) Mathematics Engineering Computer vision Image (mathematics)

Metrics

6
Cited By
0.00
FWCI (Field Weighted Citation Impact)
10
Refs
0.14
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Machine Fault Diagnosis Techniques
Physical Sciences →  Engineering →  Control and Systems Engineering
Seismic Imaging and Inversion Techniques
Physical Sciences →  Earth and Planetary Sciences →  Geophysics
NMR spectroscopy and applications
Physical Sciences →  Physics and Astronomy →  Nuclear and High Energy Physics

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