Distributed and Sequential Algorithms for Bioinformatics by K. Erciyes

Author:K. Erciyes
Language: eng
Format: epub
Publisher: Springer International Publishing, Cham

9.2.2 Hidden Markov Models

A Markov chain is a state machine where the future state is only dependent on the current state and the probability of moving from the current state to the future state. The sum of the probabilities of transitions from a state is equal to unity. Formally, a Markov chain is a triplet (Q, p, A) such that Q is a finite set of states from an alphabet .

p is the initial state probabilities.

A is the state transition probabilities with elements for transition from state s to t such that ).

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