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20182026
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eess.SP2026

(Sequential) Joint Detection and Estimation: Classic Results and New Directions

Dominik Reinhard, Abdelhak M. Zoubir

We provide an overview of the problem of jointly testing two hypotheses and estimating a parameter of the selected model. Such problems arise in a variety of applications. First, w…

eess.SP2026

Minimax Optimal Procedures for Joint Detection and Estimation

Dominik Reinhard, Michael Fauß, Abdelhak M. Zoubir

We investigate the problem of jointly testing a pair of composite hypotheses and, depending on the test result, estimating a random parameter under distributional uncertainties. Sp…

eess.SP2021

Asymptotically Optimal Procedures for Sequential Joint Detection and Estimation

Dominik Reinhard, Michael Fauß, Abdelhak M. Zoubir

We investigate the problem of jointly testing multiple hypotheses and estimating a random parameter of the underlying distribution in a sequential setup. The aim is to jointly infe…

eess.SP2020

Distributed Joint Detection and Estimation: A Sequential Approach

Dominik Reinhard, Michael Fauß, Abdelhak M. Zoubir

We investigate the problem of jointly testing two hypotheses and estimating a random parameter based on data that is observed sequentially by sensors in a distributed network. In p…

eess.SP2020

Bayesian Sequential Joint Detection and Estimation under Multiple Hypotheses

Dominik Reinhard, Michael Fauß, Abdelhak M. Zoubir

We consider the problem of jointly testing multiple hypotheses and estimating a random parameter of the underlying distribution. This problem is investigated in a sequential setup…

eess.SP2018

Bayesian Sequential Joint Detection and Estimation

Dominik Reinhard, Michael Fauss, Abdelhak M. Zoubir

Joint detection and estimation refers to deciding between two or more hypotheses and, depending on the test outcome, simultaneously estimating the unknown parameters of the underly…