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  2. Forward–backward algorithm - Wikipedia

    en.wikipedia.org/wiki/Forward–backward_algorithm

    The forward–backward algorithm is an inference algorithm for hidden Markov models which computes the posterior marginals of all hidden state variables given a sequence of observations/emissions ::=, …,, i.e. it computes, for all hidden state variables {, …,}, the distribution ( | :).

  3. Hidden Markov model - Wikipedia

    en.wikipedia.org/wiki/Hidden_Markov_model

    Figure 1. Probabilistic parameters of a hidden Markov model (example) X — states y — possible observations a — state transition probabilities b — output probabilities. In its discrete form, a hidden Markov process can be visualized as a generalization of the urn problem with replacement (where each item from the urn is returned to the original urn before the next step). [7]

  4. Baum–Welch algorithm - Wikipedia

    en.wikipedia.org/wiki/Baum–Welch_algorithm

    In electrical engineering, statistical computing and bioinformatics, the Baum–Welch algorithm is a special case of the expectation–maximization algorithm used to find the unknown parameters of a hidden Markov model (HMM). It makes use of the forward-backward algorithm to compute the statistics for the expectation step. The Baum–Welch ...

  5. Forward algorithm - Wikipedia

    en.wikipedia.org/wiki/Forward_algorithm

    The forward algorithm, in the context of a hidden Markov model (HMM), is used to calculate a 'belief state': the probability of a state at a certain time, given the history of evidence. The process is also known as filtering .

  6. Viterbi algorithm - Wikipedia

    en.wikipedia.org/wiki/Viterbi_algorithm

    The general algorithm involves message passing and is substantially similar to the belief propagation algorithm (which is the generalization of the forward-backward algorithm). With an algorithm called iterative Viterbi decoding , one can find the subsequence of an observation that matches best (on average) to a given hidden Markov model.

  7. Category:Markov models - Wikipedia

    en.wikipedia.org/wiki/Category:Markov_models

    Hidden Markov models (8 P) M. Markov networks (8 P) Pages in category "Markov models" ... Forward–backward algorithm; G. Gene prediction;

  8. List of graph theory topics - Wikipedia

    en.wikipedia.org/wiki/List_of_graph_theory_topics

    Graphical model. Bayesian network; D-separation; Markov random field; Tree decomposition (Junction tree) and treewidth; Graph triangulation (see also Chordal graph) Perfect order; Hidden Markov model. Baum–Welch algorithm; Viterbi algorithm; Incidence matrix; Independent set problem; Knowledge representation. Conceptual graph; Mind map; Level ...

  9. Category:Hidden Markov models - Wikipedia

    en.wikipedia.org/wiki/Category:Hidden_Markov_models

    Island algorithm; L. Layered hidden Markov model This page was last edited on 30 March 2013, at 04:46 (UTC). Text is available under the Creative Commons ...