enow.com Web Search

Search results

  1. Results from the WOW.Com Content Network
  2. 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]

  3. Markov model - Wikipedia

    en.wikipedia.org/wiki/Markov_model

    A hidden Markov model is a Markov chain for which the state is only partially observable or noisily observable. In other words, observations are related to the state of the system, but they are typically insufficient to precisely determine the state. Several well-known algorithms for hidden Markov models exist.

  4. Markov chain - Wikipedia

    en.wikipedia.org/wiki/Markov_chain

    The Markov chain forecasting models utilize a variety of settings, from discretizing the time series, [107] to hidden Markov models combined with wavelets, [106] and the Markov chain mixture distribution model (MCM).

  5. Hidden Markov random field - Wikipedia

    en.wikipedia.org/wiki/Hidden_Markov_random_field

    The main difference with a hidden Markov model is that neighborhood is not defined in 1 dimension but within a network, i.e. is allowed to have more than the two neighbors that it would have in a Markov chain. The model is formulated in such a way that given , are independent (conditional independence of the observable variables given the ...

  6. Markov property - Wikipedia

    en.wikipedia.org/wiki/Markov_property

    The term Markov assumption is used to describe a model where the Markov property is assumed to hold, such as a hidden Markov model. A Markov random field extends this property to two or more dimensions or to random variables defined for an interconnected network of items. [1] An example of a model for such a field is the Ising model. A discrete ...

  7. Markov renewal process - Wikipedia

    en.wikipedia.org/wiki/Markov_renewal_process

    The process is Markovian only at the specified jump instants, justifying the name semi-Markov. [1] [2] [3] (See also: hidden semi-Markov model.) A semi-Markov process (defined in the above bullet point) in which all the holding times are exponentially distributed is called a continuous-time Markov chain. In other words, if the inter-arrival ...

  8. Markovian discrimination - Wikipedia

    en.wikipedia.org/wiki/Markovian_discrimination

    There are two primary classes of Markov models, visible Markov models and hidden Markov models, which differ in whether the Markov chain generating token sequences is assumed to have its states fully determined by each generated token (the visible Markov models) or might also have additional state (the hidden Markov models). With a visible ...

  9. Models of DNA evolution - Wikipedia

    en.wikipedia.org/wiki/Models_of_DNA_evolution

    (i) In the context of Markov chains, transition is the general term for the change between two states. (ii) In the context of nucleotide changes in DNA sequences , transition is a specific term for the exchange between either the two purines (A ↔ G) or the two pyrimidines (C ↔ T) (for additional details, see the article about transitions in ...