• DocumentCode
    1506039
  • Title

    Computing the bivariate Gaussian probability integral

  • Author

    Chandramouli, R. ; Ranganathan, N.

  • Author_Institution
    Center for Microelectron. Res., Univ. of South Florida, Tampa, FL, USA
  • Volume
    6
  • Issue
    6
  • fYear
    1999
  • fDate
    6/1/1999 12:00:00 AM
  • Firstpage
    129
  • Lastpage
    131
  • Abstract
    In signal processing applications, it is often required to compute the integral of the bivariate Gaussian probability density function (PDF) over the four quadrants. When the mean of the random variables are nonzero, computing the closed form solution to these integrals with the usual techniques of integration is infeasible. Many numerical solutions have been proposed; however, the accuracy of these solutions depends on various constraints. In this work, we derive the closed form solution to this problem using the characteristic function method. The solution is derived in terms of the well-known confluent hypergeometric function. When the mean of the random variables is zero, the solution is shown to reduce to a known result for the value of the integral over the first quadrant. The solution is implementable in software packages such as MAPLE.
  • Keywords
    gamma distribution; integral equations; random processes; signal processing; software packages; MAPLE; PDF; bivariate Gaussian probability integral; characteristic function method; closed form solution; confluent hypergeometric function; mean; nonzero random variables; numerical solutions; probability density function; signal processing applications; software packages; Closed-form solution; Laplace equations; Nonlinear equations; Probability density function; Random variables; Signal analysis; Signal processing; Software packages; Stochastic processes;
  • fLanguage
    English
  • Journal_Title
    Signal Processing Letters, IEEE
  • Publisher
    ieee
  • ISSN
    1070-9908
  • Type

    jour

  • DOI
    10.1109/97.763142
  • Filename
    763142