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Acceleration of hidden Markov model fitting using graphical processing units, with application to low-frequency tremor classification

Author: Stoltz, M ; Stoltz, George G ; Obara, K ; Wang, T ; Bryant, D Date: Nov 2021 Hidden Markov models (HMMs) are general purpose models for time-series data widely used across the sciences because of their flexibility and elegance. Fitting HMMs can often be computationally demanding and time consuming, particularly when ... Read more

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Browsing by Subject "Computationally intensive methods"

Browsing by Subject "Computationally intensive methods"

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