Memorias de investigación
Communications at congresses:
Sequential Bayes factor testing: a new framework for decision fusion.
Year:2019

Research Areas
  • Sensor networks

Information
Abstract
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.
International
Si
Congress
2019 IEEE 20th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)
970
Place
Cannes
Reviewers
Si
ISBN/ISSN
978-1-5386-6528-2
10.1109/SPAWC.2019.8815408
Start Date
02/07/2019
End Date
05/07/2019
From page
1
To page
5
2019 IEEE 20th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)
Participants

Research Group, Departaments and Institutes related
  • Creador: Centro o Instituto I+D+i: Centro de I+d+i en Procesado de la Información y Telecomunicaciones
  • Grupo de Investigación: Grupo de Aplicaciones del Procesado de Señal (GAPS)
  • Departamento: Señales, Sistemas y Radiocomunicaciones