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CSDA
2007
116views more  CSDA 2007»
13 years 9 months ago
Exploring the state sequence space for hidden Markov and semi-Markov chains
The knowledge of the state sequences that explain a given observed sequence for a known hidden Markovian model is the basis of various methods that may be divided into three categ...
Yann Guédon
SFM
2007
Springer
14 years 3 months ago
Tackling Large State Spaces in Performance Modelling
Stochastic performance models provide a powerful way of capturing and analysing the behaviour of complex concurrent systems. Traditionally, performance measures for these models ar...
William J. Knottenbelt, Jeremy T. Bradley
NIPS
2003
13 years 10 months ago
Inferring State Sequences for Non-linear Systems with Embedded Hidden Markov Models
We describe a Markov chain method for sampling from the distribution of the hidden state sequence in a non-linear dynamical system, given a sequence of observations. This method u...
Radford M. Neal, Matthew J. Beal, Sam T. Roweis
ICCV
2001
IEEE
14 years 11 months ago
People Tracking Using Hybrid Monte Carlo Filtering
Particle filters are used for hidden state estimation with nonlinear dynamical systems. The inference of 3-d human motion is a natural application, given the nonlinear dynamics of...
Kiam Choo, David J. Fleet