A Hidden Markov Model (HMM) is a statistical model that is used to describe systems that are assumed to be a Markov process with hidden states. It is particularly useful in fields such as speech recognition, bioinformatics, and time series analysis. Here are the key components and concepts associated with HMMs: ### Key Components 1. **States**: HMMs consist of a set of hidden states.

Ancestors (6)

  1. Bioinformatics
  2. Mathematical and theoretical biology
  3. Applied mathematics
  4. Fields of mathematics
  5. Mathematics
  6. Home

View article source

Discussion (0)

New discussion

There are no discussions about this article yet.

Articles by others on the same topic (0)

There are currently no matching articles.
See all articles in the same topic Create my own version