— This work deals with a group of mobile sensors sampling a spatiotemporal random field whose mean is unknown and covariance is known up to a scaling parameter. The Bayesian pos...
— Representation of knowledge within a neural model is an active field of research involved with the development of alternative structures, training algorithms, learning modes an...
This paper describes a technique for the probabilistic self-localization of a sensor network based on noisy inter-sensor range data. Our method is based on a number of parallel in...
In real sensor network deployments, spatial distributions of sensors are usually far from being uniform. Such networks often contain regions without enough sensor nodes, which we ...
Determination of the functions of all expressed proteins represents one of the major upcoming challenges in computational molecular biology. Since subcellular location plays a cru...
Robert F. Murphy, Michael V. Boland, Meel Velliste