Title :
Universal source polarization and sparse recovery
Author_Institution :
Ecole Polytech. Fed. de Lausanne, Lausanne, Switzerland
fDate :
Aug. 30 2010-Sept. 3 2010
Abstract :
Polar codes allow to perform lossless compression of i.i.d. sources at the lowest rate with low encoding and decoding complexity. In this paper, it is shown that for binary sources, there exist “universal polar codes” which can compress any source of low enough entropy, without requiring knowledge of the source distribution. While this result does not extend to q-ary sources, it is shown how it extends to q-ary sources which belong to a restricted family. An analogy between this family and BECs in channel polarization is discussed. Finally, an application of the universal source polarization results to sparse data recovery is proposed.
Keywords :
binary codes; data compression; entropy codes; polarisation; BEC; channel polarization; entropy; source compression; source distribution; sparse data recovery; universal polar codes; universal source polarization; Complexity theory; Compounds; Compressed sensing; Decoding; Encoding; Extraterrestrial measurements; Sensors;
Conference_Titel :
Information Theory Workshop (ITW), 2010 IEEE
Conference_Location :
Dublin
Print_ISBN :
978-1-4244-8262-7
Electronic_ISBN :
978-1-4244-8263-4
DOI :
10.1109/CIG.2010.5592875