Block-Sparsity: Coherence and Efficient Recovery
| dc.creator | Eldar, Yonina C. | |
| dc.creator | Bolcskei, Helmut | |
| dc.date | 2008-12-01 | |
| dc.date.accessioned | 2026-07-07T12:08:19Z | |
| dc.date.available | 2026-07-07T12:08:19Z | |
| dc.description | We consider compressed sensing of block-sparse signals, i.e., sparse signals that have nonzero coefficients occuring in clusters. Based on an uncertainty relation for block-sparse signals, we define a block-coherence measure and we show that a block-version of the orthogonal matching pursuit algorithm recovers block k-sparse signals in no more than k steps if the block-coherence is sufficiently small. The same condition on block-sparsity is shown to guarantee successful recovery through a mixed l2/l1 optimization approach. The significance of the results lies in the fact that making explicit use of block-sparsity can yield better reconstruction properties than treating the signal as being sparse in the conventional sense thereby ignoring the additional structure in the problem. | |
| dc.description | Submitted to ICASSP 2009 | |
| dc.identifier | https://arxiv.org/abs/0812.0329 | |
| dc.identifier | http://arxiv.org/abs/0812.0329 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/209275 | |
| dc.subject | Information Theory | |
| dc.title | Block-Sparsity: Coherence and Efficient Recovery | |
| dc.type | text |