This paper derives a near optimal distributed Kalman filter to estimate a large-scale random field monitored by a network of N sensors. The field is described by a sparsely con...
It is crucial to study basic principles that support adaptive and scalable retrieval functions in large networked environments such as the Web, where information is distributed am...
In this paper, we apply the auction-based theories in economics to camera networks. We develop a set of auction protocols to do camera active control (pan/tilt/zoom) intelligently...
Particle filters (PFs) are powerful samplingbased inference/learning algorithms for dynamic Bayesian networks (DBNs). They allow us to treat, in a principled way, any type of prob...
Arnaud Doucet, Nando de Freitas, Kevin P. Murphy, ...
—Cognitive Radio Networks (CRNs) have recently emerged as a promising technology to improve spectrum utilization by allowing secondary users to dynamically access idle primary ch...