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Hidden Markov Models
Section 3 - Page 1
Summary
HMMs, described by a vector and two matrices ( ,A,B) are of great
value in describing real systems since, although usually only an
approximation, they are amenable to analysis. Commonly solved
problems are:
- Matching the most likely system to a sequence of
observations -evaluation, solved using the forward algorithm;
- determining the hidden sequence most likely to have
generated a sequence of observations - decoding, solved using
the Viterbi algorithm;
- determining the model parameters most likely to have
generated a sequence of observations - learning, solved using
the forward-backward algorithm.
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