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NIPS
2004
13 years 9 months ago
Dynamic Bayesian Networks for Brain-Computer Interfaces
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...
Pradeep Shenoy, Rajesh P. N. Rao
HYBRID
2003
Springer
14 years 25 days ago
Estimation of Distributed Hybrid Systems Using Particle Filtering Methods
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...
Xenofon D. Koutsoukos, James Kurien, Feng Zhao
CVPR
2010
IEEE
14 years 3 months ago
Dynamic Texture Recognition based on Distributions of Spacetime Oriented Structure
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...
Konstantinos Derpanis, Richard Wildes
SIAMCOMP
2010
83views more  SIAMCOMP 2010»
13 years 6 months ago
Reaching and Distinguishing States of Distributed Systems
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...
Robert M. Hierons
CDC
2009
IEEE
132views Control Systems» more  CDC 2009»
14 years 10 days ago
Q-learning and Pontryagin's Minimum Principle
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 ...
Prashant G. Mehta, Sean P. Meyn