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“…After removing the undesirable interferences, seismic data can be modeled as the convolution between the source wavelet w(t) and reflectivity series r(t) in the form as [10], [15], [16]: (1) where ϵ(t) is an additive random noise. Using a convolution symbol, we can rewrite it as:…”

confidence: 99%

“…After removing the undesirable interferences, seismic data can be modeled as the convolution between the source wavelet w(t) and reflectivity series r(t) in the form as [10], [15], [16]: (1) where ϵ(t) is an additive random noise. Using a convolution symbol, we can rewrite it as:…”

confidence: 99%

“…We first test the proposed method in numerical experiments. Compared with synthetic experiments in [10] and [15], we designed the sparse reflectivity series randomly instead of using fixed positions, which makes more sense for the non-stationary seismic applications. Table I shows the comparisons of the similarity measurement between ground truth and inverted reflectivity with different SNRs.…”

confidence: 99%