Viterbi Algorithm: Dynamic Programming, Algorithm, Likelihood Function, Markov Information Source, Hidden Markov Model, Information Theory, Error Detection and Correction - Tapa blanda

Sinopsis

Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. The Viterbi algorithm is a dynamic programming algorithm for finding the most likely sequence of hidden states – called the Viterbi path – that results in a sequence of observed events, especially in the context of Markov information sources, and more generally, hidden Markov models. The forward algorithm is a closely related algorithm for computing the probability of a sequence of observed events. These algorithms belong to the realm of information theory. The algorithm makes a number of assumptions. First, both the observed events and hidden events must be in a sequence. This sequence often corresponds to time. Second, these two sequences need to be aligned, and an instance of an observed event needs to correspond to exactly one instance of a hidden event. Third, computing the most likely hidden sequence up to a certain point t must depend only on the observed event at point t, and the most likely sequence at point t − 1. These assumptions are all satisfied in a first-order hidden Markov model.

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