Denoising of desert seismic signal based on synchrosqueezing transform and Adaboost algorithm
Author:
Funder
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Subject
Geophysics
Link
http://link.springer.com/content/pdf/10.1007/s11600-020-00408-1.pdf
Reference24 articles.
1. Anvari R, Siahsar MAN, Gholtashi S, Roshandel Kahoo A, Mohammadi M (2017) Seismic random noise attenuation using synchrosqueezed wavelet transform and low-rank signal matrix approximation. IEEE Trans Geosci Remote Sens 55(11):6574–6581. https://doi.org/10.1109/TGRS.2017.2730228
2. Bekara M, van der Baan M (2009) Random and coherent noise attenuation by empirical mode decomposition. Geophysics 74(5):V89–V98. https://doi.org/10.1190/1.3157244
3. Chen Y (2017) Fast dictionary learning for noise attenuation of multidimensional seismic data. Geophys J Int 209(1):21–31. https://doi.org/10.1093/gji/ggw492
4. Chen Y (2018) Fast waveform detection for microseismic imaging using unsupervised machine learning. Geophys J Int 215(2):1185–1199. https://doi.org/10.1093/GJI/GGY348
5. Chen Y, Ma J (2014) Random noise attenuation by f-x empirical-mode decomposition predictive filtering. Geophysics 79(3):81–91. https://doi.org/10.1190/GEO2013-0080.1
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