We describe an approach to building brain-computer interfaces (BCI) based on graphical models for probabilistic inference and learning. We show how a dynamic Bayesian network (DBN...
Abstract. Networked embedded systems are composed of a large number of components that interact with the physical world via a set of sensors and actuators, have their own computati...
This paper addresses the challenge of recognizing dynamic
textures based on their observed visual dynamics.
Typically, the term dynamic texture is used with reference
to image s...
Some systems interact with their environment at physically distributed interfaces, called ports, and in testing such a system it is normal to place a tester at each port. Each test...
Abstract— Q-learning is a technique used to compute an optimal policy for a controlled Markov chain based on observations of the system controlled using a non-optimal policy. It ...