Deterministic Construction of Sparse Sensing Matrices via Finite Geometry

@article{Li2014DeterministicCO,
  title={Deterministic Construction of Sparse Sensing Matrices via Finite Geometry},
  author={Shuxing Li and Gennian Ge},
  journal={IEEE Transactions on Signal Processing},
  year={2014},
  volume={62},
  pages={2850-2859}
}
Compressed sensing is a novel sampling technique that provides a fundamentally new approach to data acquisition. Comparing with the traditional method, compressed sensing asserts that a sparse signal can be reconstructed from very few measurements. A central problem in compressed sensing is the construction of sensing matrices. While random sensing matrices have been studied intensively, only a few deterministic constructions are known. As a long-standing subject in combinatorial design theory… CONTINUE READING
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