Exploiting prior knowledge, we use Bayesian estimation to localize a source heard by a fixed sensor network. The method has two main aspects: Firstly, the probability density fun...
We consider a traffic-groomed optical network consisting of N nodes arranged in tandem. This optical network is modeled by a tandem queueing network of multi-rate loss queues with...
Alicia Nicki Washington, Chih-Chieh Hsu, Harry G. ...
—Users querying massive social networks or RDF databases are often not 100% certain about what they are looking for due to the complexity of the query or heterogeneity of the dat...
We present an efficient algorithm for the approximate median selection problem. The algorithm works in-place; it is fast and easy to implement. For a large array it returns, with ...
In this paper, we present a novel entropy estimator for a given set of samples drawn from an unknown probability density function (PDF). Counter to other entropy estimators, the e...