Perturbation Analysis of ObSTP for Compressed Sensing
- Citation Author(s):
-
Yongfei Liu
(Qinghai Normal University)
- Submitted by:
- Fei Liu
- Last updated:
- DOI:
- 10.21227/ab9k-bg47
- Data Format:
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Abstract
Many algorithms for compressed sensing are studied. The common guarantee for the reconstruction algorithm is restricted isometry property (RIP), which is shown to only hold under ideal assumptions. However, in practice, more than one ideal condition is often violated and there is no RIP-based guarantee application. Based on this discrepancy, we propose a new oblique subspace thresholding pursuit (ObSTP) algorithm. It is guaranteed by the restricted biorthogonality property (RBOP) which requires no ideal assumptions. The ObSTP is an integration of the oblique pursuits and the subspace thresholding pursuit technique. The simulation results show that the ObSTP algorithm has better performance.
Instructions:
Many algorithms for compressed sensing are studied. The common guarantee for the reconstruction algorithm is restricted isometry property (RIP), which is shown to only hold under ideal assumptions. However, in practice, more than one ideal condition is often violated and there is no RIP-based guarantee application. Based on this discrepancy, we propose a new oblique subspace thresholding pursuit (ObSTP) algorithm. It is guaranteed by the restricted biorthogonality property (RBOP) which requires no ideal assumptions. The ObSTP is an integration of the oblique pursuits and the subspace thresholding pursuit technique. The simulation results show that the ObSTP algorithm has better performance.
