Name
Abstract | ||
|---|---|---|
The solution to the problem of seismic signals segmentation constitutes a very interesting and challenging task. The main difficulty in solving this problem is attributed to the fact that both the statistical properties of seismic noise, as well the characteristics of the recorded events are in general unknown. In this paper, by exploiting the particular nature of the signals we are treating, and by using some interesting properties that obeys a difference based test statistic as well as its ingredients, we propose an approach that results in a robust and efficient automatic detection method. From a series of experiments we have conducted in both synthetic and real seismic data, the effectiveness of the proposed technique is confirmed. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/ICASSP.2012.6288788 | Acoustics, Speech and Signal Processing |
Keywords | Field | DocType |
signal detection,statistical analysis,automatic detection method,difference based test statistic,real seismic data,seismic noise,seismic signals segmentation,statistical properties,synthetic seismic data | Seismic inversion,Test statistic,Detection theory,Pattern recognition,Computer science,Segmentation,Signal-to-noise ratio,Seismic noise,Robustness (computer science),Seismic wave,Artificial intelligence | Conference |
ISSN | ISBN | Citations |
1520-6149 E-ISBN : 978-1-4673-0044-5 | 978-1-4673-0044-5 | 1 |
PageRank | References | Authors |
0.37 | 1 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Erion-Vasilis M. Pikoulis | 1 | 4 | 3.21 |
| Emmanouil Z. Psarakis | 2 | 98 | 5.36 |