Deep reinforcement learning has recorded remarkable performance in diverse application
areas of artificial intelligence: pattern recognition, robotics, object segmentation …

Statistical pattern recognition is a very active area of study andresearch, which has seen
many advances in recent years. New andemerging applications-such as data mining, web …

In this paper basic results on distributed detection are reviewed. In particular we consider
the parallel and the serial architectures in some detail and discuss the decision rules …

One of the main requirements of cognitive radio systems is the ability to reliably detect the
presence of licensed primary transmissions. Previous works on the problem of detection for …

Information fusion by utilizing multiple distributed sensors is studied in this work. Extending
the classical parallel fusion structure by incorporating the fading channel layer that is …

In this paper, we revisit the problem of fusing decisions transmitted over fading channels in a
wireless sensor network. Previous development relies on instantaneous channel state …

Most results about quantized detection rely strongly on an assumption of independence
among random variables. With this assumption removed, little is known. Thus, in this paper …

Secure message dissemination is an important issue in vehicular networks, especially
considering the vulnerability of vehicle-to-vehicle message dissemination to malicious …

For a wireless sensor network (WSN) with randomly deployed sensors, the performance of
the counting rule, where the fusion center employs the total number of detections reported …

Statistical inference is a mature research area, but distributed inference problems that arise
in the context of modern wireless sensor networks (WSNs) have new and unique features …