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
Link To Document :
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