@article{c106868043ae45cd8b55fef2efa42b3e,
title = "Nonlinear sparse-graph codes for lossy compression",
abstract = "We propose a scheme for lossy compression of discrete memoryless sources: The compressor is the decoder of a nonlinear channel code, constructed from a sparse graph. We prove asymptotic optimality of the scheme for any separable (letter-by-letter) bounded distortion criterion. We also present a suboptimal compression algorithm, which exhibits near-optimal performance for moderate block lengths.",
keywords = "Discrete memoryless sources, Lossy data compression, Rate-distortion theory, Source-channel coding duality, Sparse-graph codes",
author = "Ankit Gupta and Sergio Verd{\'u}",
note = "Funding Information: Manuscript received June 24, 2007; revised January 08, 2009. Current version published April 22, 2009. This work was supported in part by the National Science Foundation under Grant CCR-0312839. The material in this paper was presented in part at the IEEE Information Theory Workshop, Lake Tahoe, CA, September 2007. The authors are with the Department of Electrical Engineering, Princeton University, Princeton NJ 08544 USA (e-mail:ankitg@princeton.edu; verdu@princeton.edu). Communicated by M. Effros, Associate Editor for Source Coding. Color versions of Figures 1–7 in this paper are available online at http://iee-explore.ieee.org. Digital Object Identifier 10.1109/TIT.2009.2016040",
year = "2009",
doi = "10.1109/TIT.2009.2016040",
language = "English (US)",
volume = "55",
pages = "1961--1975",
journal = "IRE Professional Group on Information Theory",
issn = "0018-9448",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "5",
}