Difference between revisions of "HMM"

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... In process of being edited by [[User:Dmovshov|Dana Movshovitz-Attias]] ...
 
... In process of being edited by [[User:Dmovshov|Dana Movshovitz-Attias]] ...
  
[[Category:: Method | ]]
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[[Category::Method | ]]
Hidden Markov Models (HMMs) are statistical models that are used for representing two or more stochastic processes with a [http://en.wikipedia.org/wiki/Markov_property Markov property].
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Hidden Markov Models (HMMs) are statistical models that are used for representing stochastic [http://en.wikipedia.org/wiki/Markov_process Markov processes] with hidden states.
  
<!-- in which the system being modeled is assumed to be a Markov process with unobserved (hidden) states. -->
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The output of the model is observable and dependent on the hidden states. The process is governed by '''transition probabilities''' which determine the probability of moving between states, and '''emission probabilities''' which determine the output of each state.
  
 
[http://en.wikipedia.org/wiki/Hidden_Markov_model External Link]
 
[http://en.wikipedia.org/wiki/Hidden_Markov_model External Link]

Revision as of 09:31, 29 September 2011

... In process of being edited by Dana Movshovitz-Attias ...


Hidden Markov Models (HMMs) are statistical models that are used for representing stochastic Markov processes with hidden states.

The output of the model is observable and dependent on the hidden states. The process is governed by transition probabilities which determine the probability of moving between states, and emission probabilities which determine the output of each state.

External Link

Relevant Papers