• DocumentCode
    3047540
  • Title

    Unknown noise estimation with DPM model and its application

  • Author

    Shuxia, Guo ; Bo, Yang ; Ning, Liu

  • Author_Institution
    Northwestern Polytech. Univ., Xi´´an, China
  • fYear
    2010
  • fDate
    21-23 Oct. 2010
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Dirichlet process mixture (DPM) model, which is the state-of-the-art Bayesian nonparametric model in Statistics, was introduced here. We explored its ability to model and estimate nongaussian unknown noise and applied it to dynamic estimation problem. The algorithm was given and a real world example of GPS estimation problem demonstrated the efficiency of our algorithm.
  • Keywords
    Bayes methods; noise; nonparametric statistics; Bayesian nonparametric model; DPM model; Dirichlet process mixture model; GPS estimation problem; dynamic estimation problem; nongaussian unknown noise; unknown noise estimation; Bayesian methods; Computational modeling; Estimation; Global Positioning System; Mathematical model; Noise; Signal processing algorithms; Dirichlet Process Mixture; dynamic estimation; multipath; noise estimation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Wireless Communications and Signal Processing (WCSP), 2010 International Conference on
  • Conference_Location
    Suzhou
  • Print_ISBN
    978-1-4244-7556-8
  • Electronic_ISBN
    978-1-4244-7554-4
  • Type

    conf

  • DOI
    10.1109/WCSP.2010.5633494
  • Filename
    5633494
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3047540