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Activity Number: 197
Type: Contributed
Date/Time: Monday, July 30, 2007 : 2:00 PM to 3:50 PM
Sponsor: Biometrics Section
Abstract - #308571
Title: Mutual Information for the Mixture of Two Multivariate Distributions
Author(s): Walfredo Javier*+ and Arjun K. Gupta
Companies: Southern University-Baton Rouge and Bowling Green State University
Address: , Baton Rouge, LA, 70813,
Keywords: mutual information ; mixture of two normal distributions ; normal linear and quadratic forms
Abstract:

Mutual Information for a multivariate random vector is a measure of dependence among the component random vectors; it is zero when the components are independent, positive otherwise. The paper derives the mutual information for a mixture of two multivariate normal distributions without the assumption that the two component normal distributions be widely separated. This is accomplished by partitioning the sample space into two disjoint subspaces in each of which the series expansion for ln(1+y) is valid.

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Revised September, 2007