In this paper, we study the problem of decomposing gates in fanin-unbounded or K-bounded networks such that the K-input LUT mapping solutions computed by a depthoptimal mapper hav...
The MAP (maximum a posteriori hypothesis) problem in Bayesian networks is to find the most likely states of a set of variables given partial evidence on the complement of that set...
8 The training of some types of neural networks leads to separable non-linear least squares problems. These problems may be9 ill-conditioned and require special techniques. A robus...
Suppose that an organization O wants to do the following: to reveal only part of its network map; to filter unwanted traffic passing through its network; and to route, to the righ...
We introduce a new rational function (RF) model for radial lens distortion in wide-angle and catadioptric lenses, which allows the simultaneous linear estimation of motion and len...