# 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

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## 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
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