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Likelihood ratios and inference for Poisson channels

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Date
2013
Link to item file
http://arxiv.org/abs/0709.1211v3
Dewey
Probabilités et mathématiques appliquées
Sujet
extended De Bruijn identities; mutual information; Malliavin calculus; Bayesian estimation; Poisson process
Journal issue
IEEE Transactions on Information Theory
Volume
59
Number
10
Publication date
2013
Article pages
6261-6272
Publisher
IEEE
DOI
http://dx.doi.org/10.1109/TIT.2013.2268911
URI
https://basepub.dauphine.fr/handle/123456789/7108
Collections
  • CEREMADE : Publications
Metadata
Show full item record
Author
Réveillac, Anthony
Type
Article accepté pour publication ou publié
Abstract (EN)
In recent years, infinite-dimensional methods have been introduced for the Gaussian channels estimation. The aim of this paper is to study the application of similar methods to Poisson channels. In particular we compute the Bayesian estimator of a Poisson channel using the likelihood ratio and the discrete Malliavin gradient. This algorithm is suitable for numerical implementation via the Monte-Carlo scheme. As an application we provide an new proof of the formula obtained recently by Guo, Shamai and Verdu\'u relating some derivatives of the input-output mutual information of a time-continuous Poisson channel and the conditional mean estimator of the input. These results are then extended to mixed Gaussian-Poisson channels.

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