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Sensing the radio spectrum is an essential feature of cognitive radio. What is mostly important for a cognitive transmitter is to know the power spectral density at the location of its intended receiver and of the primary receivers. This requires, as a whole, knowledge of the spatial distribution of the power spectral density, an information that could be delivered by a network of sensors distributed...
The observations gathered by the individual nodes of a sensor network may be unreliable due to malfunctioning, observation noise or low battery level. Global reliability is typically recovered by collecting all the measurements in a fusion center which takes proper decisions. However, centralized networks are more vulnerable and prone to congestion around the sink nodes. To relax the congestion problem,...
In most sensor network applications, the vector containing the observations gathered by the sensors lies in a space of dimension equal to the number of nodes, typically because of observation noise, even though the useful signal belongs to a subspace of much smaller dimension. This motivates smoothing or rank reduction. We formulate a convex optimization problem, where we incorporate a fidelity constraint...
Historically, land grant universities and their colleges of agriculture have been discipline driven in both their curricula and research agendas. Critics call for interdisciplinary approaches to undergraduate curriculum. Concomitantly, sustainable agriculture (SA) education is beginning to emerge as a way to address many complex social and environmental problems. University of California at Davis...
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