• DocumentCode
    1024049
  • Title

    Estimating random integrals from noisy observations: sampling designs and their performance

  • Author

    Bucklew, James A. ; Cambinis, S.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Wisconsin Univ., Madison, WI, USA
  • Volume
    34
  • Issue
    1
  • fYear
    1988
  • fDate
    1/1/1988 12:00:00 AM
  • Firstpage
    111
  • Lastpage
    127
  • Abstract
    The problem of estimating a weighted average of a random process from noisy observations at a finite number of sampling points is considered. The performance of sampling designs with optimal or suboptimal, but easily computable, estimator coefficients is studied. Several examples and special cases are studied, including additive independent noise, nonlinear distortion with noise, and quantization noise
  • Keywords
    information theory; random processes; signal processing; additive independent noise; information theory; noisy observations; nonlinear distortion with noise; quantization noise; random integrals estimation; sampling designs; signal processing; Additive noise; Estimation error; H infinity control; Information theory; Integral equations; Nonlinear distortion; Quantization; Random processes; Sampling methods; Signal sampling;
  • fLanguage
    English
  • Journal_Title
    Information Theory, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9448
  • Type

    jour

  • DOI
    10.1109/18.2609
  • Filename
    2609
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1024049