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 ellipsoidal uncertainty set.Because of the limited bandwidth