• DocumentCode
    2929009
  • Title

    A statistical analysis of adaptive quantization based on causal past

  • Author

    Yu, Bin

  • Author_Institution
    Dept. of Stat., California Univ., Berkeley, CA, USA
  • fYear
    1995
  • fDate
    17-22 Sep 1995
  • Firstpage
    375
  • Abstract
    A statistical estimation framework is proposed for adaptive quantization based on causal past. Different estimation methods are given for the marginal density based on the quantized sample. For a stationary and ergodic source process, if its marginal density is in a parametric family with a dimension less than the quantization level, then “adaptation” can be achieved when the sample size is large, i.e., the marginal density can be estimated consistently
  • Keywords
    adaptive signal processing; encoding; estimation theory; quantisation (signal); statistical analysis; adaptive quantization; causal past; dimension; encoding; ergodic source process; estimation methods; marginal density; parametric family; quantization level; quantized sample; sample size; stationary source process; statistical analysis; statistical estimation; Equations; Gaussian processes; Maximum likelihood estimation; Monte Carlo methods; Quantization; Statistical analysis; Stochastic processes; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Theory, 1995. Proceedings., 1995 IEEE International Symposium on
  • Conference_Location
    Whistler, BC
  • Print_ISBN
    0-7803-2453-6
  • Type

    conf

  • DOI
    10.1109/ISIT.1995.550362
  • Filename
    550362