학술논문
Robust Sequential Testing of Multiple Hypotheses in Distributed Sensor Networks
Document Type
Conference
Author
Source
2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) Acoustics, Speech and Signal Processing (ICASSP), 2018 IEEE International Conference on. :4394-4398 Apr, 2018
Subject
Language
ISSN
2379-190X
Abstract
The problem of sequential multiple hypothesis testing in a distributed sensor network is considered and two algorithms are proposed: the Consensus + Innovations Matrix Sequential Probability Ratio Test $(\mathcal{CI}\mathrm{MSPRT}$ for multiple simple hypotheses and the robust Least-Favorable-Density- $\mathcal{CI}\mathrm{MSPRT}$ for hypotheses with uncertainties in the corresponding distributions. Simulations are performed to verify and evaluate the performance of both algorithms under different network conditions and noise contaminations.