Hidden Markov models hmms and partially observable Markov decision processes pomdps provide useful tools for modeling dynamical systems. They are particularly useful for represent...
We present a learning algorithm for non-parametric hidden Markov models with continuous state and observation spaces. All necessary probability densities are approximated using sa...
Hidden Markov models (HMMs) have received considerable attention in various communities (e.g, speech recognition, neurology and bioinformatic) since many applications that use HMM...
Geophysics research has been faced with a growing need for automated techniques with which to process large quantities of data. A successful tool must meet a number of requirements...
Hidden Markov models (HMMs) have proven useful in various aspects of speech technology from automatic speech recognition through speech synthesis, speech segmentation and grapheme...
Udochukwu Kalu Ogbureke, Peter Cahill, Julie Carso...