A constructive proof of the existence of Viterbi processes
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Since the early days of digital communication, hidden Markov models (HMMs) have now been also routinely used in speech recognition, processing of natural languages, images, and in bioinformatics. In an HMM (X_i,Y_i)_i> 1, observations X_1,X_2,... are assumed to be conditionally independent given an "explanatory" Markov process Y_1,Y_2,..., which itself is not observed; moreover, the conditional distribution of X_i depends solely on Y_i. Central to the theory and applications of HMM is the Viterbi algorithm to find a maximum a posteriori (MAP) estimate q_1:n=(q_1,q_2,...,q_n) of Y_1:n given observed data x_1:n. Maximum a posteriori paths are also known as Viterbi paths or alignments. Recently, attempts have been made to study the behavior of Viterbi alignments when n→∞. Thus, it has been shown that in some special cases a well-defined limiting Viterbi alignment exists. While innovative, these attempts have relied on rather strong assumptions and involved proofs which are existential. This work proves the existence of infinite Viterbi alignments in a more constructive manner and for a very general class of HMMs.
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