• DocumentCode
    2707598
  • Title

    On global optimality of gradient descent algorithms for fixed-rate scalar multiple description quantizer design

  • Author

    Dumitrescu, Sorina ; Wu, Xiaolin

  • Author_Institution
    Dept. of Electr. & Comput. Eng., McMaster Univ., Hamilton, Ont., Canada
  • fYear
    2005
  • fDate
    29-31 March 2005
  • Firstpage
    388
  • Lastpage
    397
  • Abstract
    We prove that Trushkin´s (1982) sufficient conditions for the global optimality of a locally optimal fixed-rate scalar quantizer also ensure the global optimality of a locally optimal fixed-rate multiple description scalar quantizer of convex codecells, with respect to a fixed index assignment. This result also holds for the fixed-rate multiresolution scalar quantizer of convex codecells. As a consequence the well-known log-concave pdf condition can be extended to the multiple description and multiresolution case.
  • Keywords
    codes; gradient methods; optimisation; probability; vector quantisation; convex codecells; fixed index assignment; fixed-rate quantizer design; global optimality; gradient descent algorithms; log-concave pdf condition; multiresolution scalar quantizer; scalar multiple description quantizer; Algorithm design and analysis; Data compression; Probability density function; Probability distribution; Quantization; Random variables; Sufficient conditions;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Data Compression Conference, 2005. Proceedings. DCC 2005
  • ISSN
    1068-0314
  • Print_ISBN
    0-7695-2309-9
  • Type

    conf

  • DOI
    10.1109/DCC.2005.60
  • Filename
    1402200