TY - GEN
T1 - A single-shot approach to lossy source coding under logarithmic loss
AU - Shkel, Yanina
AU - Verdu, Sergio
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/8/10
Y1 - 2016/8/10
N2 - This paper studies the problem of lossy source coding with a specific distortion measure: logarithmic loss. The focus of this paper is on the single-shot approach which exposes the connection between lossy source coding with log-loss and lossless source coding. Point-to-point bounds, including the single-shot fundamental limit for average as well as excess distortion, are presented. Two multi-terminal problems are addressed: coding with side information (Wyner-Ziv), and multiple descriptions coding. In both cases, the application of the Shannon-McMillan Theorem to the single-shot bounds immediately yields the rate-distortion function and the rate distortion-region for stationary and ergodic sources.
AB - This paper studies the problem of lossy source coding with a specific distortion measure: logarithmic loss. The focus of this paper is on the single-shot approach which exposes the connection between lossy source coding with log-loss and lossless source coding. Point-to-point bounds, including the single-shot fundamental limit for average as well as excess distortion, are presented. Two multi-terminal problems are addressed: coding with side information (Wyner-Ziv), and multiple descriptions coding. In both cases, the application of the Shannon-McMillan Theorem to the single-shot bounds immediately yields the rate-distortion function and the rate distortion-region for stationary and ergodic sources.
UR - http://www.scopus.com/inward/record.url?scp=84985916563&partnerID=8YFLogxK
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U2 - 10.1109/ISIT.2016.7541840
DO - 10.1109/ISIT.2016.7541840
M3 - Conference contribution
AN - SCOPUS:84985916563
T3 - IEEE International Symposium on Information Theory - Proceedings
SP - 2953
EP - 2957
BT - Proceedings - ISIT 2016; 2016 IEEE International Symposium on Information Theory
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2016 IEEE International Symposium on Information Theory, ISIT 2016
Y2 - 10 July 2016 through 15 July 2016
ER -