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Optimal Rate-Exponent Region for a Class of Hypothesis Testing Against Conditional Independence Problems

Information Theory 2019-04-08 v1 math.IT Statistics Theory Statistics Theory

Abstract

We study a class of distributed hypothesis testing against conditional independence problems. Under the criterion that stipulates minimization of the Type II error rate subject to a (constant) upper bound ϵ\epsilon on the Type I error rate, we characterize the set of encoding rates and exponent for both discrete memoryless and memoryless vector Gaussian settings.

Keywords

Cite

@article{arxiv.1904.03028,
  title  = {Optimal Rate-Exponent Region for a Class of Hypothesis Testing Against Conditional Independence Problems},
  author = {Abdellatif Zaidi and Inaki Estella Aguerri},
  journal= {arXiv preprint arXiv:1904.03028},
  year   = {2019}
}

Comments

Submitted for publication to the IEEE Information Theory Workshop, ITW 2019. arXiv admin note: substantial text overlap with arXiv:1811.03933

R2 v1 2026-06-23T08:30:26.265Z