• DocumentCode
    1033524
  • Title

    Distributed learning in wireless sensor networks

  • Author

    Predd, Joel B. ; Kulkarni, Sanjeev R. ; Poor, H. Vincent

  • Author_Institution
    Princeton Univ., NJ, USA
  • Volume
    23
  • Issue
    4
  • fYear
    2006
  • fDate
    7/1/2006 12:00:00 AM
  • Firstpage
    56
  • Lastpage
    69
  • Abstract
    This paper discusses nonparametric distributed learning. After reviewing the classical learning model and highlighting the success of machine learning in centralized settings, the challenges that wireless sensor networks (WSN) pose for distributed learning are discussed, and research aimed at addressing these challenges is surveyed.
  • Keywords
    learning (artificial intelligence); reviews; telecommunication computing; wireless sensor networks; distributed inference; machine learning; nonparametric distributed learning; wireless sensor networks; Bandwidth; Delay estimation; Intelligent networks; Machine learning; Parametric statistics; Robustness; Sensor phenomena and characterization; Signal design; Statistical distributions; Wireless sensor networks;
  • fLanguage
    English
  • Journal_Title
    Signal Processing Magazine, IEEE
  • Publisher
    ieee
  • ISSN
    1053-5888
  • Type

    jour

  • DOI
    10.1109/MSP.2006.1657817
  • Filename
    1657817