hidden Markov model


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hidden Markov model

[¦hid·ən ′mär·kəf ‚mäd·əl]
(mathematics)
A finite-state machine that is also a doubly stochastic process involving at least two levels of uncertainty: a random process associated with each state, and a Markov chain, which characterizes the probabilistic relationship among the states in terms of how likely one state is to follow another.
References in periodicals archive ?
"Network security situation prediction method based on hidden Markov model," Journal of Central South University (Science and Technology), vol.46, no.10, pp.3689-3695, 2015.
Continuous density hidden Markov models (CD-HMM) were used for the creation of a Lithuanian recognizer by using an open code software toolkit HTK v.3.2 (Hidden Markov Toolkit) [8].
The direct evaluation method, in comparison, requires O([N.sup.T+k-1]) calculations where N is the number of states, T is the length of observational sequence, and k is the order of the Hidden Markov Model.
Lee, "Hidden Markov model and self-organizing map applied to exploration of movement behaviors of Daphnia magna (Cladocera: Daphniidae)," Journal of the Korean Physical Society, vol.
Kemmerer, "Using hidden Markov models to evaluate the risks of intrusions: system architecture and model validation," in Lecture Notes in Computer Science, pp.
The current study explored to predict driver's eye-off road duration in different driving scenarios by building Hidden Markov Models (HMM) using driver's visual behavior.
The R package "HMM" was used for Hidden Markov Model related computations [24].
The rest of this paper proceeds as follows: "Literature" section discusses the forward-discount puzzle, "The hidden Markov model" section presents the hidden Markov model, "Analysis of Results" section analyses the initial results, "Exogenous Influences on Regime SwitchingProbabilities" section considers exogenous influences on the probability of switching from one regime to another, and "Conclusion" section concludes.
The first step is to submit the initial values of the Hidden Markov Model's parameters to the algorithm.
Hidden Markov Models (HMMs) [1] are one of the statistical modelling tools showing great success and have been widely used in diverse application fields such as speech processing [2], machine maintenance [3], acoustics [4], biosciences [5], handwriting and text recognition [6], and image processing [7].
The major classification models used were, Neural Networks (NN), Support Vector Machine (SVM), and Hidden Markov Model (HMM).