Spectral clustering is one of the most widely used techniques for extracting the underlying global structure of a data set. Compressed sensing and matrix completion have emerged a...
This paper considers the decomposition of a complex matrix as the product of several sets of semi-unitary matrices and upper triangular matrices in iterative manner. The inner mos...
We show that randomization can lead to significant improvements for a few fundamental problems in distributed tracking. Our basis is the count-tracking problem, where there are k...
— For the single-group multicast scenario, where K users are served with the same data by a base station equipped with N antennas, we present two beamforming algorithms which out...
Raphael Hunger, David A. Schmidt, Michael Joham, A...
We propose several novel localized algorithms to construct energy efficient routing structures for homogeneous wireless ad hoc networks, where all nodes have same maximum transmis...