Regularization plays a central role in the analysis of modern data, where non-regularized fitting is likely to lead to over-fitted models, useless for both prediction and interpre...
The sensor scheduling problem can be formulated as a controlled hidden Markov model and this paper solves the problem when the state, observation and action spaces are continuous....
Sumeetpal S. Singh, Nikolaos Kantas, Ba-Ngu Vo, Ar...
One of the simplest sensor network models has one single underlying Gaussian source of interest, observed by many sensors, subject to independent Gaussian observation noise. The se...
In this paper, we consider a deterministic timed continuous Petri net model where conflicts at places are solved by using stationary routing parameters. We show how to compute the...
A new means of action selection via utility fusion is introduced as an alternative to both sensor fusion and command fusion. Distributed asynchronous behaviors indicate the utility...