Perturbation Analysis of ObSTP for Compressed Sensing

Yongfei Liu

Abstract


Many algorithms for compressed sensing are studied. And 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 illustrate that the ObSTP algorithm has better performance.

Keywords


Compressed sensing, subspace thresholding pursuit, restricted isometry property, restricted biorthogonality property, perturbation

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DOI: https://doi.org/10.18686/esta.v10i3.497

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