Compressive sampling and lossy compression: Do random measurements provide an efficient method of representing sparse signals?

Vivek K. Goyal, Alyson K. Fletcher, Sundeep Rangan

Research output: Contribution to journalArticlepeer-review

Abstract

A recent work investigated whether random measurements of sparse signals provide an efficient method of representing sparse signals. How the random measurements are encoded into bits are the basis for the performance of the source coding. Even very weak forms of universality are precluded using familiar forms of quantization. The recent work also showed that recovery of the sparsity pattern is asymptotically impossible and that the mean-squared error peformance is far from optimal.

Original languageEnglish (US)
Pages (from-to)48-56
Number of pages9
JournalIEEE Signal Processing Magazine
Volume25
Issue number2
DOIs
StatePublished - Mar 2008

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering
  • Applied Mathematics

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