• DocumentCode
    1282480
  • Title

    Compressibility of Deterministic and Random Infinite Sequences

  • Author

    Amini, Arash ; Unser, Michael ; Marvasti, Farokh

  • Author_Institution
    Electr. Eng. Dept., Sharif Univ. of Technol., Tehran, Iran
  • Volume
    59
  • Issue
    11
  • fYear
    2011
  • Firstpage
    5193
  • Lastpage
    5201
  • Abstract
    We introduce a definition of the notion of compressibility for infinite deterministic and i.i.d. random sequences which is based on the asymptotic behavior of truncated subsequences. For this purpose, we use asymptotic results regarding the distribution of order statistics for heavy-tail distributions and their link with α -stable laws for 1 <; α <; 2 . In many cases, our proposed definition of compressibility coincides with intuition. In particular, we prove that heavy-tail (polynomial decaying) distributions fulfill the requirements of compressibility. On the other hand, exponential decaying distributions like Laplace and Gaussian do not. The results are such that two compressible distributions can be compared with each other in terms of their degree of compressibility.
  • Keywords
    random sequences; statistical analysis; asymptotic behavior; compressibility; deterministic infinite sequences; heavy-tail distribution; order statistics; random infinite sequences; random sequences; truncated subsequences; Approximation methods; Indexes; Markov processes; Polynomials; Random sequences; Random variables; Compressible prior; heavy-tail distribution; order statistics; stable law;
  • fLanguage
    English
  • Journal_Title
    Signal Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1053-587X
  • Type

    jour

  • DOI
    10.1109/TSP.2011.2162952
  • Filename
    5961647