Abstract
This correspondence presents an average case denoising performance analysis for SP, CoSaMP, and IHT algorithms. This analysis considers the recovery of a noisy signal, with the assumptions that it is corrupted by an additive random zero-mean white Gaussian noise and has a K-sparse representation with respect to a known dictionary bf D. The proposed analysis is based on the RIP, establishing a near-oracle performance guarantee for each of these algorithms. Beyond bounds for the reconstruction error that hold with high probability, in this work we also provide a bound for the average error.
Original language | English |
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Article number | 6071013 |
Pages (from-to) | 1465-1468 |
Number of pages | 4 |
Journal | IEEE Transactions on Signal Processing |
Volume | 60 |
Issue number | 3 |
DOIs | |
State | Published - Mar 2012 |
Externally published | Yes |
Keywords
- Additive white noise
- Gaussian noise
- compressed sensing
- signal denoising
- signal reconstruction
- signal representations