| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 5102785 | Physica A: Statistical Mechanics and its Applications | 2017 | 15 Pages |
Abstract
This work analyzes the correlation between the seismic signal entropy and the Compressive Sensing (CS) recovery index. The recovery index measures the quality of a signal reconstructed by the CS method. We analyze the performance of two CS algorithms: the â1-MAGIC and the Fast Bayesian Compressive Sensing (BCS). We have observed a negative correlation between the performance of CS and seismic signal entropy. Signals with low entropy have small recovery index in their reconstruction by CS. The rationale behind our finding is: a sparse signal is easy to recover by CS and, besides, a sparse signal has low entropy. In addition, â1-MAGIC shows a more significant correlation between entropy and CS performance than Fast BCS.
Related Topics
Physical Sciences and Engineering
Mathematics
Mathematical Physics
Authors
Eberton S. Marinho, Tiago C. Rocha, Gilberto Corso, Liacir S. Lucena,