Projects per year
Reconstruction of an undersampled signal is at the root of compressive sensing: when is an algorithm capable of reconstructing the signal? what quality is achievable? and how much time does reconstruction require? We have considered the worst-case performance of the smoothed ℓ0 norm reconstruction algorithm in a noiseless setup. Through an empirical tuning of its parameters, we have improved the phase transition (capabilities) of the algorithm for fixed quality and required time. In this paper, we present simulation results that show a phase transition surpassing that of the theoretical ℓ1 approach: the proposed modified algorithm obtains 1-norm phase transition with greatly reduced required computation time.
|Title of host publication||Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on|
|Publication status||Published - 2013|
|Event||2013 IEEE International Conference on Acoustics, Speech, and Signal Processing - Vancouver, Canada|
Duration: 26 May 2013 → 31 May 2013
Conference number: 38
|Conference||2013 IEEE International Conference on Acoustics, Speech, and Signal Processing|
|Period||26/05/2013 → 31/05/2013|
|Series||I E E E International Conference on Acoustics, Speech and Signal Processing. Proceedings|
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SparSig: Sparse Signal Processing in Wireless Communications
Larsen, T., Jensen, S. H., Arildsen, T., Fyhn, K., Pankiewicz, P. J., Li, P. & Jensen, T.
01/01/2010 → 27/09/2013