Abstract
A matching pursuit method using a Bayesian approach is introduced for recovering a set of sparse signals with common support from a set of their measurements. This method performs Bayesian estimates of joint-sparse signals even when the distribution of active elements is not known. It utilizes only the a priori statistics of noise and the sparsity rate of the signal, which are estimated without user intervention. The method utilizes a greedy approach to determine the approximate MMSE estimate of the joint-sparse signals. Simulation results demonstrate the superiority of the proposed estimator.
| Original language | English (US) |
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| Title of host publication | 2014 Proceedings of the 22nd European Signal Processing Conference, EUSIPCO 2014 |
| Publisher | European Signal Processing Conference, EUSIPCO |
| Pages | 1741-1745 |
| Number of pages | 5 |
| ISBN (Electronic) | 9780992862619 |
| State | Published - Nov 10 2014 |
| Event | 22nd European Signal Processing Conference, EUSIPCO 2014 - Lisbon, Portugal Duration: Sep 1 2014 → Sep 5 2014 |
Publication series
| Name | European Signal Processing Conference |
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| ISSN (Print) | 2219-5491 |
Other
| Other | 22nd European Signal Processing Conference, EUSIPCO 2014 |
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| Country/Territory | Portugal |
| City | Lisbon |
| Period | 09/1/14 → 09/5/14 |
Bibliographical note
Publisher Copyright:© 2014 EURASIP.
ASJC Scopus subject areas
- Signal Processing
- Electrical and Electronic Engineering