TY - GEN
T1 - Fundamental limits of almost lossless analog compression
AU - Wu, Yihong
AU - Verdú, Sergio
PY - 2009
Y1 - 2009
N2 - In Shannon theory, lossless source coding deals with the optimal compression of discrete sources. Compressed sensing is a lossless coding strategy for analog sources by means of multiplication by real-valued matrices. In this paper we study almost lossless analog compression for analog memoryless sources in an information-theoretic framework, in which the compressor is not constrained to linear transformations but it satisfies various regularity conditions such as Lipschitz continuity. The fundamental limit is shown to be the information dimension proposed by Rényi in 1959.
AB - In Shannon theory, lossless source coding deals with the optimal compression of discrete sources. Compressed sensing is a lossless coding strategy for analog sources by means of multiplication by real-valued matrices. In this paper we study almost lossless analog compression for analog memoryless sources in an information-theoretic framework, in which the compressor is not constrained to linear transformations but it satisfies various regularity conditions such as Lipschitz continuity. The fundamental limit is shown to be the information dimension proposed by Rényi in 1959.
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U2 - 10.1109/ISIT.2009.5205734
DO - 10.1109/ISIT.2009.5205734
M3 - Conference contribution
AN - SCOPUS:70449473616
SN - 9781424443130
T3 - IEEE International Symposium on Information Theory - Proceedings
SP - 359
EP - 363
BT - 2009 IEEE International Symposium on Information Theory, ISIT 2009
T2 - 2009 IEEE International Symposium on Information Theory, ISIT 2009
Y2 - 28 June 2009 through 3 July 2009
ER -