Comments on `Detector relative efficiencies in the presence ofLaplace noise' by M.I. Dadi and J.R. Marks II

In the above-titled paper (see ibid., vol.AES-23, p.568-82, July 1987) M.I. Dadi and J.R. Marks II studied the relative efficiencies of the Neyman-Pearson optimal detector with respect to the linear and sign detectors, for the detection of a constant signal in additive Laplace noise. By applying the central limit theorem, they derived expressions for three types of asymptotic relative efficiencies (AREs). However, as noted in the above paper, the Gaussian approximation to the sign detector fails to yield the correct asymptotic efficiency. The commenter derives the correct ARE of the optimal detector with respect to the sign detector for the Laplace noise     

On distributed detection with correlated sensors: two examples

The authors study the effect of correlated noise on the performance of a distributed detection system. They consider a suboptimal scheme by assuming that the local sensors have the same operating point, and that the distribution of the sensor observation is symmetric. This implies that the joint distribution of the sensor decisions, and therefore the fusion rule, are symmetric functions of the sensor decisions. The detection of a known signal in additive Gaussian noise and in Laplacian noise are considered. In both cases, system performance deteriorates when the correlation between the sensor noises is positive and increasing, whereas the performance improves considerably when the correlation is negative and increasing in magnitude