• DocumentCode
    1755382
  • 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 Electr. & Comput. Eng., Curtin Univ., Bentley, WA, Australia
  • Volume
    61
  • Issue
    8
  • fYear
    2015
  • fDate
    Aug. 2015
  • Firstpage
    4475
  • Lastpage
    4485
  • Abstract
    In this paper, we extend the notion of Cauchy-Schwarz divergence to point processes and establish that the Cauchy-Schwarz divergence between the probability densities of two Poisson point processes is half the squared L2-distance between their intensity functions. Extension of this result to mixtures of Poisson point processes and, in the case where the intensity functions are Gaussian mixtures, closed form expressions for the Cauchy-Schwarz divergence are presented. Our result also implies that the Bhattacharyya distance between the probability distributions of two Poisson point processes is equal to the square of the Hellinger distance between their intensity measures. We illustrate the result via a sensor management application where the system states are modeled as point processes.
  • Keywords
    Gaussian processes; probability; sensors; Bhattacharyya distance; Cauchy-Schwarz divergence; Gaussian mixture; Hellinger distance; Poisson point process; closed form expression; intensity function; probability density; probability distribution; sensor management application; Atmospheric measurements; Density measurement; Measurement units; Particle measurements; Probability distribution; Random variables; Standards; Poisson point process; information divergence; random finite sets;
  • fLanguage
    English
  • Journal_Title
    Information Theory, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9448
  • Type

    jour

  • DOI
    10.1109/TIT.2015.2441709
  • Filename
    7118202