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Minimum Complexity Pursuit for Universal Compressed Sensing

contributor authorJalali, Shirin
contributor authorMaleki, Ali
contributor authorBaraniuk, R.G.
date accessioned2020-03-12T18:42:12Z
date available2020-03-12T18:42:12Z
date issued2014
identifier issn0018-9448
identifier other6719502.pdf
identifier urihttp://libsearch.um.ac.ir:80/fum/handle/fum/967439?locale-attribute=en&show=full
formatgeneral
languageEnglish
publisherIEEE
titleMinimum Complexity Pursuit for Universal Compressed Sensing
typeJournal Paper
contenttypeMetadata Only
identifier padid8001427
subject keywordscompressed sensing
subject keywordsinformation theory
subject keywordsmeasurement errors
subject keywordsmeasurement uncertainty
subject keywordsKolmogorov complexity
subject keywordsOccam razor
subject keywordsabstract algorithm
subject keywordsalgorithmic information theory
subject keywordsgeneral abstract meanings
subject keywordsgroup sparsity
subject keywordshigh-dimensional signals
subject keywordsleveraging
subject keywordsmeasurement noise
subject keywordsminimum complexity pursuit
subject keywordsnascent field
subject keywordsrandomized samples
subject keywordssignal recovery
subject keywordssimple structured objects
subject keywordsuniversal algorithms
subject keywordsuniversal compressed sensing
subject keywordsApproximation algorithms
subject keywordsComplexity theory
subject keywordsComputers
subject keywordsNoise
subject keywordsNoise
identifier doi10.1109/TIT.2014.2302005
journal titleInformation Theory, IEEE Transactions on
journal volume60
journal issue4
filesize603722
citations0


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