A Gradient-Based Method for Robust Sensor Selection in Hypothesis Testing

A Gradient-Based Method for Robust Sensor Selection in Hypothesis Testing

This paper considers the binary Gaussian distribution robust hypothesis testing under a Bayesian optimal criterion in the wireless sensor network (WSN). The distribution covariance matrix under each hypothesis is known, while the distribution mean vector under each hypothesis drifts in an ellipsoida...

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Bibliographic Details
Main Authors: Ting Ma, Bo Qian, Dunbiao Niu, Enbin Song, Qingjiang Shi
Format: Article
Language:English
Published: MDPI AG 2020-01-01
Series:Sensors
Subjects:
wireless sensor network
robust sensor selection
hypothesis testing
chernoff distance
danskin’s theorem
orthogonal constraint-preserving gradient algorithm
Online Access:https://www.mdpi.com/1424-8220/20/3/697

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https://www.mdpi.com/1424-8220/20/3/697

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