Robust Sequential Testing of Multiple Hypotheses in Distributed Sensor Networks
Robust Sequential Testing of Multiple Hypotheses in Distributed Sensor Networks
复制标题
分布式传感器网络中多个假设的鲁棒顺序测试
DOI：
10.1109/icassp.2018.8461895
复制
发表时间：
2018
期刊：
影响因子：
--
通讯作者：
A. Zoubir
中科院分区：
文献类型：
--
作者：
Mark R. Leonard;M. Stiefel;Michael Fauss;A. Zoubir
研究了分布式传感器网络中的序贯多假设检验问题，提出了两种算法：对于多个简单假设，提出了一致性+创新矩阵序贯概率比检验算法；对于相应分布中存在不确定性的假设，提出了稳健的最小有利密度检验算法。为了验证和评估这两种算法在不同网络条件和噪声污染下的性能，进行了仿真。
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.