Nonlinear sparse-graph codes for lossy compression

Ankit Gupta, Sergio Verdú

Research output: Contribution to journalArticlepeer-review

27 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)1961-1975
Number of pages15
JournalIEEE Transactions on Information Theory
Issue number5
StatePublished - 2009

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Computer Science Applications
  • Library and Information Sciences


  • Discrete memoryless sources
  • Lossy data compression
  • Rate-distortion theory
  • Source-channel coding duality
  • Sparse-graph codes


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