The Cauchy-Schwarz divergence for Poisson point processes
| Autor: | Hoang, Hung Gia, Vo, Ba-Ngu, Vo, Ba-Tuong, Mahler, Ronald |
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| Rok vydání: | 2013 |
| Předmět: | |
| Zdroj: | IEEE Trans. Inf. Theory (2015), vol. 61, no. 8, pp. 4475-4485 |
| Druh dokumentu: | Working Paper |
| DOI: | 10.1109/TIT.2015.2441709 |
| Popis: | 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 $\mathbf{L^{2}}$-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 Bhattachryaa 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. Comment: Two colunms, 11 pages, 5 figures. This paper has been published in the IEEE Transaction on Information Theory. Part of the paper was presented at the 2014 IEEE Workshop on Statistical Signal Processing, Gold Coast, Australia |
| Databáze: | arXiv |
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