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
Link To Document