DocumentCode :
1790780
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 ECE, Curtin Univ., Bentley, WA, Australia
fYear :
2014
fDate :
June 29 2014-July 2 2014
Firstpage :
240
Lastpage :
243
Abstract :
Information theoretic divergences are fundamental tools used to measure the difference between the information conveyed by two random processes. In this paper, we show that the Cauchy-Schwarz divergence between two Poisson point processes is the half the squared L2-distance between their respective intensity functions. Moreover, this can be evaluated in closed form when the intensities are Gaussian mixtures.
Keywords :
information theory; random processes; stochastic processes; Cauchy-Schwarz divergence; Gaussian mixtures; Poisson point processes; information theoretic divergences; intensity functions; random processes; squared L2-distance; Approximation methods; Conferences; Density measurement; Measurement units; Random variables; Signal processing; Vectors; Poisson point process; information theoretic divergence; random finite sets;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Statistical Signal Processing (SSP), 2014 IEEE Workshop on
Conference_Location :
Gold Coast, VIC
Type :
conf
DOI :
10.1109/SSP.2014.6884620
Filename :
6884620
Link To Document :
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