Some Results on the Vector Gaussian Hypothesis Testing Problem

2020/05/14 by Escamilla, Pierre, Zaidi, Abdellatif, Wigger, Michèle
#FOS: Computer and information sciences #Information Theory (cs.IT)

paper · doi:10.48550/arxiv.2005.06822

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.

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