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Descripción
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| We propose using a Bayes factor sequential hypothesis test for the decision fusion problem in wireless sensor networks, in which several sensors send a report to a fusion center so that a global decision is taken. This problem is frequently modeled in current literature as a hypothesis test from Bernoulli samples. We propose using a sequential composite hypothesis test based on Bayes Factor using Beta distributions as prior distributions. We obtain closed form expressions for the distributions, which allows us to develop a very efficient algorithm to implement our approach. When we validate our approach via simulations, we observe that, when compared to the common counting rule, our algorithm provides a lower average error and requires a smaller number of samples to make a decision. | |
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Internacional
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Si |
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Nombre congreso
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2019 IEEE 20th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC) |
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Tipo de participación
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970 |
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Lugar del congreso
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Cannes |
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Revisores
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Si |
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ISBN o ISSN
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978-1-5386-6528-2 |
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DOI
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10.1109/SPAWC.2019.8815408 |
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Fecha inicio congreso
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02/07/2019 |
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Fecha fin congreso
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05/07/2019 |
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Desde la página
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1 |
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Hasta la página
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5 |
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Título de las actas
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2019 IEEE 20th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC) |