Support agnostic Bayesian matching pursuit for block sparse signals

Handle URI:
http://hdl.handle.net/10754/564708
Title:
Support agnostic Bayesian matching pursuit for block sparse signals
Authors:
Masood, Mudassir ( 0000-0003-0462-7874 ) ; Al-Naffouri, Tareq Y.
Abstract:
A fast matching pursuit method using a Bayesian approach is introduced for block-sparse signal recovery. This method performs Bayesian estimates of block-sparse signals even when the distribution of active blocks is non-Gaussian or unknown. It is agnostic to the distribution of active blocks in the signal and utilizes a priori statistics of additive noise and the sparsity rate of the signal, which are shown to be easily estimated from data and no user intervention is required. The method requires a priori knowledge of block partition and utilizes a greedy approach and order-recursive updates of its metrics to find the most dominant sparse supports to determine the approximate minimum mean square error (MMSE) estimate of the block-sparse signal. Simulation results demonstrate the power and robustness of our proposed estimator. © 2013 IEEE.
KAUST Department:
Electrical Engineering Program
Publisher:
Institute of Electrical and Electronics Engineers (IEEE)
Journal:
2013 IEEE International Conference on Acoustics, Speech and Signal Processing
Conference/Event name:
2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013
Issue Date:
May-2013
DOI:
10.1109/ICASSP.2013.6638540
Type:
Conference Paper
ISSN:
15206149
ISBN:
9781479903566
Appears in Collections:
Conference Papers; Electrical Engineering Program

Full metadata record

DC FieldValue Language
dc.contributor.authorMasood, Mudassiren
dc.contributor.authorAl-Naffouri, Tareq Y.en
dc.date.accessioned2015-08-04T07:13:13Zen
dc.date.available2015-08-04T07:13:13Zen
dc.date.issued2013-05en
dc.identifier.isbn9781479903566en
dc.identifier.issn15206149en
dc.identifier.doi10.1109/ICASSP.2013.6638540en
dc.identifier.urihttp://hdl.handle.net/10754/564708en
dc.description.abstractA fast matching pursuit method using a Bayesian approach is introduced for block-sparse signal recovery. This method performs Bayesian estimates of block-sparse signals even when the distribution of active blocks is non-Gaussian or unknown. It is agnostic to the distribution of active blocks in the signal and utilizes a priori statistics of additive noise and the sparsity rate of the signal, which are shown to be easily estimated from data and no user intervention is required. The method requires a priori knowledge of block partition and utilizes a greedy approach and order-recursive updates of its metrics to find the most dominant sparse supports to determine the approximate minimum mean square error (MMSE) estimate of the block-sparse signal. Simulation results demonstrate the power and robustness of our proposed estimator. © 2013 IEEE.en
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en
dc.subjectBayesian matching pursuiten
dc.subjectBlock sparse signalsen
dc.subjectcompressed sensingen
dc.subjectSABMPen
dc.subjectsparse signal recoveryen
dc.titleSupport agnostic Bayesian matching pursuit for block sparse signalsen
dc.typeConference Paperen
dc.contributor.departmentElectrical Engineering Programen
dc.identifier.journal2013 IEEE International Conference on Acoustics, Speech and Signal Processingen
dc.conference.date26 May 2013 through 31 May 2013en
dc.conference.name2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013en
dc.conference.locationVancouver, BCen
dc.contributor.institutionEE Department, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabiaen
kaust.authorMasood, Mudassiren
kaust.authorAl-Naffouri, Tareq Y.en
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