Publication:
COMPRESSIVE PARAMETER ESTIMATION VIA APPROXIMATE MESSAGE PASSING

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dc.contributor.advisorMarco F. Duarte
dc.contributor.authorHamzehei, Shermin
dc.contributor.departmentUniversity of Massachusetts Amherst
dc.contributor.departmentElectrical & Computer Engineering
dc.date2024-03-28T19:55:54.000
dc.date.accessioned2024-04-26T18:28:41Z
dc.date.available2024-04-26T18:28:41Z
dc.date.submittedFebruary
dc.date.submitted2020
dc.description.abstractThe literature on compressive parameter estimation has been mostly focused on the use of sparsity dictionaries that encode a discretized sampling of the parameter space; these dictionaries, however, suffer from coherence issues that must be controlled for successful estimation. To bypass such issues with discretization, we propose the use of statistical parameter estimation methods within the Approximate Message Passing (AMP) algorithm for signal recovery. Our method leverages the recently proposed use of custom denoisers in place of the usual thresholding steps (which act as denoisers for sparse signals) in AMP. We introduce the design of analog denoisers that are based on statistical parameter estimation algorithms, and we focus on two commonly used examples: frequency estimation and bearing estimation, coupled with the Root MUSIC estimation algorithm. We first analyze the performance of the proposed analog denoiser for signal recovery, and then link the performance in signal estimation to that of parameter estimation. Numerical experiments show significant improvements in estimation performance versus previously proposed approaches for compressive parameter estimation.
dc.description.degreeMaster of Science in Electrical and Computer Engineering (M.S.E.C.E.)
dc.identifier.doihttps://doi.org/10.7275/15995042
dc.identifier.orcidhttps://orcid.org/0000-0002-6824-3637
dc.identifier.urihttps://hdl.handle.net/20.500.14394/33939
dc.relation.urlhttps://scholarworks.umass.edu/cgi/viewcontent.cgi?article=1923&context=masters_theses_2&unstamped=1
dc.source.statuspublished
dc.subjectCompressive Sensing
dc.subjectParameter estimation
dc.subjectApproximate Message Passing
dc.subjectSignal Processing
dc.titleCOMPRESSIVE PARAMETER ESTIMATION VIA APPROXIMATE MESSAGE PASSING
dc.typeopenaccess
dc.typearticle
dc.typethesis
digcom.contributor.authorisAuthorOfPublication|email:shamzehei@engin.umass.edu|institution:University of Massachusetts Amherst|Hamzehei, Shermin
digcom.identifiermasters_theses_2/877
digcom.identifier.contextkey15995042
digcom.identifier.submissionpathmasters_theses_2/877
dspace.entity.typePublication
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