Empirical recovery performance of fourier-based deterministic compressed sensing

Please use this identifier to cite or link to this item: https://knowledgecommons.lakeheadu.ca/handle/2453/484

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DC Field	Value	Language
dc.contributor.advisor	Yu, Nam Yul	-
dc.contributor.author	Li, Ying	-
dc.date.accessioned	2014-01-22T16:36:04Z	-
dc.date.available	2014-01-22T16:36:04Z	-
dc.date.created	2013	-
dc.date.issued	2014-01-22	-
dc.identifier.uri	http://knowledgecommons.lakeheadu.ca/handle/2453/484	-
dc.description.abstract	Compressed sensing is a novel technique where one can recover sparse signals from the undersampled measurements. Mathematically, measuring an N-dimensional signal...	en_US
dc.language.iso	en_US	en_US
dc.subject	Compressed sensing	en_US
dc.subject	Noisy compressed sensing	en_US
dc.subject	Haar wavelet transform	en_US
dc.subject	Chirp sensing codes	en_US
dc.subject	Orthogonal matching pursuit algorithm	en_US
dc.title	Empirical recovery performance of fourier-based deterministic compressed sensing	en_US
dc.type	Thesis	en_US
etd.degree.name	M.Sc.	en_US
etd.degree.level	Master	en_US
etd.degree.discipline	Engineering : Electrical & Computer	en_US
etd.degree.grantor	Lakehead University	en_US
dc.contributor.committeemember	Wei, Ruizhong	-
dc.contributor.committeemember	Naser, Hassan	-
Appears in Collections:	Electronic Theses and Dissertations from 2009

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