Math @ Duke

Publications [#319386] of Henry Pfister
Papers Published
 Zhang, F; Pfister, HD, Compressed sensing and linear codes over real numbers,
2008 Information Theory and Applications Workshop  Conference Proceedings, ITA
(October, 2008),
pp. 558561, ISBN 1424426707 [doi]
(last updated on 2018/10/17)
Abstract: Compressed sensing (CS) is a relatively new area of signal processing and statistics that focuses on signal reconstruction from a small number of linear (e.g., dot product) measurements. In this paper, we analyze CS using tools from coding theory because CS can also be viewed as syndromebased source coding of sparse vectors using linear codes over real numbers. While coding theory does not typically deal with codes over real numbers, there is actually a very close relationship between CS and errorcorrecting codes over large discrete alphabets. This connection leads naturally to new reconstruction methods and analysis. In some cases, the resulting methods provably require many fewer measurements than previous approaches.


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