Super-resolution of point sources via convex programming

@article{FernandezGranda2015SuperresolutionOP,
  title={Super-resolution of point sources via convex programming},
  author={Carlos Fernandez-Granda},
  journal={2015 IEEE 6th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)},
  year={2015},
  pages={41-44}
}
Recent work has shown that convex programming allows to recover a superposition of point sources exactly from low-resolution data as long as the sources are separated by 2/fc, where fc is the cut-off frequency of the sensing process. The proof relies on the construction of a certificate whose existence implies exact recovery. This certificate has since been used to establish that the approach is robust to noise and to analyze related problems such as compressed sensing off the grid and the… CONTINUE READING
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