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

机译:基于集合经验模式分解和小波阈值滤波的随机降噪

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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.
机译:本文提出了一种基于集合经验模式分解(EEMD)和小波阈值滤波的随机降噪方法。首先,我们已经进行了频谱分析并分析了有效信号和噪声的频带范围。其次,我们利用地震信号的EEMD方法来获得每条迹线的内在模式功能(IMF)。然后,在每条迹线的高频IMF上使用小波阈值降噪方法,以获得新的高频IMF。最后,通过将低频IMF和趋势项目上添加新的高频IMF和一起来重建所需信号。在应用我们对合成地震记录和现场数据的方法时,我们可以获得良好的结果。

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