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Compressed sensing and linear codes over real numbers
2008
2008 Information Theory and Applications Workshop
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 syndrome-based 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
doi:10.1109/ita.2008.4601055
fatcat:kodvzmq5fvbzpip6c7gibde3jm