Compressive Sensing With Prior Information: Requirements and Probabilities of Reconstruction in ${\mbi \ell}_{\bf 1}$-Minimization

@article{Miosso2013CompressiveSW,
  title={Compressive Sensing With Prior Information: Requirements and Probabilities of Reconstruction in  \$\{\mbi \ell\}_\{\bf 1\}\$-Minimization},
  author={Cristiano Jacques Miosso and Ricardo von Borries and J. H. Pierluissi},
  journal={IEEE Transactions on Signal Processing},
  year={2013},
  volume={61},
  pages={2150-2164}
}
In compressive sensing, prior information about the sparse representation's support reduces the theoretical minimum number of measurements that allows perfect reconstruction. This theoretical lower bound corresponds to the ideal reconstruction procedure based on <formula formulatype="inline"><tex Notation="TeX">${\ell_0}$</tex> </formula>-minimization, which is not practical for most real-life signals. In this paper, we show that this type of prior information also improves the probability of… CONTINUE READING

Citations

Publications citing this paper.
SHOWING 1-10 OF 23 CITATIONS, ESTIMATED 31% COVERAGE

73 Citations

0102030'14'15'16'17'18'19
Citations per Year
Semantic Scholar estimates that this publication has 73 citations based on the available data.

See our FAQ for additional information.

References

Publications referenced by this paper.
SHOWING 1-10 OF 26 REFERENCES

Compressive sensing with prior information—Theoretical lower limits in -minimization and practical signal reconstruction

  • C. J. Miosso, R. von Borries, J. H. Pierluissi
  • IEEE Trans. Signal Process., , submitted for…
  • 2011
Highly Influential
9 Excerpts

Similar Papers

Loading similar papers…