Skip to main content

# The Likelihood Encoder for Lossy Compression

## Author(s): Song, Eva C; Cuff, Paul; Poor, H Vincent

To refer to this page use: http://arks.princeton.edu/ark:/88435/pr1qj4p
 Abstract: A likelihood encoder is studied in the context of lossy source compression. The analysis of the likelihood encoder is based on the soft-covering lemma. It is demonstrated that the use of a likelihood encoder together with the soft-covering lemma yields simple achievability proofs for classical source coding problems. The cases of the point-to-point rate-distortion function, the rate-distortion function with side information at the decoder (i.e., the Wyner-Ziv problem), and the multi-terminal source coding inner bound (i.e., the Berger-Tung problem) are examined in this paper. Furthermore, a non-asymptotic analysis is used for the point-to-point case to examine the upper bound on the excess distortion provided by this method. The likelihood encoder is also related to a recent alternative technique using the properties of random binning. Publication Date: Apr-2016 Citation: Song, Eva C., Paul Cuff, and H. Vincent Poor. "The likelihood encoder for lossy compression." IEEE Transactions on Information Theory 62, no. 4 (2016): 1836-1849. doi:10.1109/TIT.2016.2529657 DOI: 10.1109/TIT.2016.2529657 ISSN: 0018-9448 EISSN: 1557-9654 Pages: 1836 - 1849 Type of Material: Journal Article Journal/Proceeding Title: IEEE Transactions on Information Theory Version: Author's manuscript

Items in OAR@Princeton are protected by copyright, with all rights reserved, unless otherwise indicated.