• DocumentCode
    3471967
  • Title

    On the role of sparsity in Compressed Sensing and random matrix theory

  • Author

    Vershynin, Roman

  • Author_Institution
    Dept. of Math., Univ. of Michigan, Ann Arbor, MI, USA
  • fYear
    2009
  • fDate
    13-16 Dec. 2009
  • Firstpage
    189
  • Lastpage
    192
  • Abstract
    We discuss applications of some concepts of compressed sensing in the recent work on invertibility of random matrices due to Rudelson and the author. We sketch an argument leading to the optimal bound ¿(N-1/2) on the median of the smallest singular value of an N × N matrix with random independent entries. We highlight the parts of the argument where sparsity ideas played a key role.
  • Keywords
    matrix algebra; signal processing; compressed sensing sparsity; optimal bound; random matrix theory; Bibliographies; Collaboration; Compressed sensing; Conferences; Entropy; Extraterrestrial measurements; Functional analysis; History; Mathematics; Sparse matrices;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2009 3rd IEEE International Workshop on
  • Conference_Location
    Aruba, Dutch Antilles
  • Print_ISBN
    978-1-4244-5179-1
  • Electronic_ISBN
    978-1-4244-5180-7
  • Type

    conf

  • DOI
    10.1109/CAMSAP.2009.5413304
  • Filename
    5413304
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3471967