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HMMHidden Markov Model
HMMHeroes of Might and Magic (gaming)
HMMMarine Medium Helicopter Squadron (US DoD)
HMMHardware Maintenance Manual
HMMHex Mica Module
HMMHazardous Materials Management
HMMHeavy Metal Maniacs
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HMMHome Management of Malaria (health strategy)
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HMMHalf Molecule Model
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HMMHub Management Module (Black Box)
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References in periodicals archive ?
A hidden Markov model uses the potential carry-trade profits to identify the most likely regime and the probability of switching from a calm regime to one of crisis for each exchange rate.
Kim, "Independent Shape Component-based Human Activity Recognition via Hidden Markov Model," Applied Intelligence, vol.
The major classification models used were, Neural Networks (NN), Support Vector Machine (SVM), and Hidden Markov Model (HMM).
According to differences between observation probability values and state transition description modes, hidden Markov chains (HMM) can be classified into discrete HMM (DHMM), semi-continuous hidden Markov model (SCHMM) and continuous hidden Markov model (CHMM).
For this purpose, some systems [4] use dynamic programming- (DP-) matching [7], whereas others [5, 8, 9] use hidden Markov models (HMMs) [10].
West, "Policy recognition in the abstract hidden Markov model," Journal of Artificial Intelligence Research, vol.
In this paper, we implemented a machine-learning based processes, the Hidden Markov Model.
Thus, we will be using a hidden Markov model with the number of successful plate appearances per game as the visible variable.
The main approaches in die paper are based on Hidden Markov Model techniques, which encode probabilistic relationships among variables of interest.
The performance of traditional feature extraction techniques and wavelet-domain based estimators was compared using Hidden Markov Model (HMM).
Additionally, the hidden Markov model can represent an arbitrary distribution for the next value of the state variables, in contrast to the Gaussian noise model that is used for the Kalman filter (Haikin 2001).
4] described a method using two complementary sorts of information from a hidden Markov model.