Abstract—We consider a certain class of large random matrices, composed of independent column vectors with zero mean and different covariance matrices, and derive asymptotically ...
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...
A local algorithm is a distributed algorithm that completes after a constant number of synchronous communication rounds. We present local approximation algorithms for the minimum ...
: Suppose we need to watch a set of targets continuously for a required period of time, and suppose we choose any number of sensors from a fixed set of sensor types and place them ...
We give improved approximation algorithms for a variety of latency minimization problems. In particular, we give a 3.591 -approximation to the minimum latency problem, improving o...