Information theoretical and algorithmic approaches to quantized compressive sensing

Research output: Contribution to journalArticlepeer-review


We study the average distortion introduced by scalar, vector, and entropy coded quantization of compressive sensing (CS) measurements. The asymptotic behavior of the underlying quantization schemes is either quantified exactly or characterized via bounds. We adapt two benchmark CS reconstruction algorithms to accommodate quantization errors, and empirically demonstrate that these methods significantly reduce the reconstruction distortion when compared to standard CS techniques.

Original languageEnglish (US)
Article number5773638
Pages (from-to)1857-1866
Number of pages10
JournalIEEE Transactions on Communications
Issue number7
StatePublished - Jul 2011


  • Compressive sensing
  • distortion rate function
  • quantization
  • subspace pursuit

ASJC Scopus subject areas

  • Electrical and Electronic Engineering


Dive into the research topics of 'Information theoretical and algorithmic approaches to quantized compressive sensing'. Together they form a unique fingerprint.

Cite this