• DocumentCode
    1790780
  • Title

    The Cauchy-Schwarz divergence for poisson point processes

  • Author

    Hung Gia Hoang ; Ba-Ngu Vo ; Ba Tuong Vo ; Mahler, Ronald

  • Author_Institution
    Dept. of ECE, Curtin Univ., Bentley, WA, Australia
  • fYear
    2014
  • fDate
    June 29 2014-July 2 2014
  • Firstpage
    240
  • Lastpage
    243
  • Abstract
    Information theoretic divergences are fundamental tools used to measure the difference between the information conveyed by two random processes. In this paper, we show that the Cauchy-Schwarz divergence between two Poisson point processes is the half the squared L2-distance between their respective intensity functions. Moreover, this can be evaluated in closed form when the intensities are Gaussian mixtures.
  • Keywords
    information theory; random processes; stochastic processes; Cauchy-Schwarz divergence; Gaussian mixtures; Poisson point processes; information theoretic divergences; intensity functions; random processes; squared L2-distance; Approximation methods; Conferences; Density measurement; Measurement units; Random variables; Signal processing; Vectors; Poisson point process; information theoretic divergence; random finite sets;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Statistical Signal Processing (SSP), 2014 IEEE Workshop on
  • Conference_Location
    Gold Coast, VIC
  • Type

    conf

  • DOI
    10.1109/SSP.2014.6884620
  • Filename
    6884620