Quantization of Sparse Representations

dc.contributor.authorBoufounos, Petros T.en_US
dc.contributor.authorBaraniuk, Richard G.en_US
dc.date.accessioned2007-01-16T20:06:46Zen_US
dc.date.available2007-01-16T20:06:46Zen_US
dc.date.issued2007-01-16en_US
dc.descriptionSummary to appear in the Proceedings of the Data Compression Conference (DCC) '07, March 27-29, 2007, Snowbird, Utahen_US
dc.description.abstractCompressive sensing (CS) is a new signal acquisition technique for sparse and compressible signals. Rather than uniformly sampling the signal, CS computes inner products with randomized basis functions; the signal is then recovered by a convex optimization. Random CS measurements are universal in the sense that the same acquisition system is sufficient for signals sparse in any representation. This paper examines the effect of quanitization of CS measurements. A careful study of stictly sparse, power-limited signals concludes that CS with scalar quantization does not use its allocated rate efficiently. The inefficiency, which is quantified, can be interpreted as the price that must be paid for the universality of the encoding system. The results in this paper complement and extend recent results on the quantization of compressive sensing measurements of compressible signals.en_US
dc.description.sponsorshipResearch supported by ONR grants N00014-06-1-0768 and N00014-06-1-0829; AFOSR grant FA9550-04-0148; DARPA grants N66001-06-1-2011 and N00014-06-1-0610; NSF grants CCF-0431150, CNS-0435425, and CNS-0520280; and the Texas Instruments Leadership University Program.en_US
dc.format.extent139380 bytesen_US
dc.format.mimetypeapplication/pdfen_US
dc.identifier.citationP. T. Boufounos and R. G. Baraniuk, "Quantization of Sparse Representations," 2007.en_US
dc.identifier.urihttps://hdl.handle.net/1911/13033en_US
dc.language.isoengen_US
dc.relation.IsPartOfSeriesRice University ECE Department Technical Report 0701en_US
dc.subjectquantizationen_US
dc.subjectcompressive sensingen_US
dc.subjectsparse signalsen_US
dc.titleQuantization of Sparse Representationsen_US
dc.typeReporten_US
dc.type.dcmiTexten_US
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