Signal And Noise Separation: Art And Science
| Autor: | Mauricio D. Sacchi, Tadeusz J. Ulrych, J. Michael Graul |
|---|---|
| Rok vydání: | 1999 |
| Předmět: |
Data processing
Noise measurement Computer science Noise (signal processing) Speech recognition Estimator Inversion (meteorology) Signal Inversion (discrete mathematics) Multiplicative noise Separable space Gradient noise Geophysics Wavelet Geochemistry and Petrology Algorithm Eigenvalues and eigenvectors |
| Zdroj: | 6th International Congress of the Brazilian Geophysical Society. |
| DOI: | 10.3997/2214-4609-pdb.215.sbgf403 |
| Popis: | The separation of signal and noise is a central issue in seismic data processing. The noise is both random and coherent in nature, the coherent part often masquerading as signal. In this tutorial, we present some approaches to signal isolation, in which stacking is a central concept. Our methodology is to transform the data to a domain where noise and signal are separable, a goal that we attain by means of inversion. We illustrate our ideas with some of our favorite transformations: wavelets, eigenvectors, and Radon transforms. We end with the notion of risk, baseball, and the Stein estimator. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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