In this paper, two modified constrained learning algorithms are proposed to obtain better generalization performance and faster convergence rate. The additional cost terms of the ...
The transmission capacity of an ad-hoc network is the maximum density of active transmitters in an unit area, given an outage constraint at each receiver for a fixed rate of transm...
Rahul Vaze, Kien T. Truong, Steven Weber, Robert W...
We propose a new algorithm for dense optical flow computation. Dense optical flow schemes are challenged by the presence of motion discontinuities. In state of the art optical flo...
We represent switching activity in VLSI circuits using a graphical probabilistic model based on Cascaded Bayesian Networks (CBN’s). We develop an elegant method for maintaining ...
Abstract—Active measurements on network paths provide endto-end network health status in terms of metrics such as bandwidth, delay, jitter and loss. Hence, they are increasingly ...