Some Results on the Vector Gaussian Hypothesis Testing Problem
Information Theory
2020-05-15 v1 math.IT
Abstract
This paper studies the problem of discriminating two multivariate Gaussian distributions in a distributed manner. Specifically, it characterizes in a special case the optimal typeII error exponent as a function of the available communication rate. As a side-result, the paper also presents the optimal type-II error exponent of a slight generalization of the hypothesis testing against conditional independence problem where the marginal distributions under the two hypotheses can be different.
Cite
@article{arxiv.2005.06822,
title = {Some Results on the Vector Gaussian Hypothesis Testing Problem},
author = {Pierre Escamilla and Abdellatif Zaidi and Michèle Wigger},
journal= {arXiv preprint arXiv:2005.06822},
year = {2020}
}
Comments
To appear in 2020 IEEE International Symposium on Information Theory, ISIT'20