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Digital Processing of Seismic Signals

Mohamed M. Al-Abasy, M. I. Dessouky, M. Abdelnaby, F. E. Abd El-Samie


The importance of seismic wave researches concentrate of the ability to predict earthquake and also obtain information on the Earth’s composition and features. Compression is the reduction of signal size to save storage capacity, transmission time, and cost. In this paper, we propose a technique for seismic signal compression and two techniques for seismic signal reconstruction. Compression is performed with a decimation process, which reduces the sampling rate. The reconstruction of the original seismic signal can be performed using inverse interpolation techniques such as maximum entropy and regularization theory. In addition, we apply compression through multiplication of a certain non-square matrix followed by a pseudo-inverse process for reconstruction. Finally we assess the quality of the reconstructed signals using quality measures such as Signal-to-Noise Ratio (SNR), segmental Signal-to-Noise Ratio (SNRseg), Spectral Distortion (SD), and Log-Likelihood Ratio (LLR).


Seismic Signal, Decimation, Maximum Entropy, Regularization Theory.

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