Iterative Viterbi decoding
id:
iterative-viterbi-decoding-274-12415564
title:
Iterative Viterbi decoding
text:
Iterative Viterbi decoding is an algorithm that spots the subsequence S of an observation O = {o1, ..., on} having the highest average probability of being generated by a given hidden Markov model M with m states. The algorithm uses a modified Viterbi algorithm as an internal step. The scaled probability measure was first proposed by John S. Bridle. An early algorithm to solve this problem, sliding window, was proposed by Jay G. Wilpon et al., 1989, with constant cost T = mn2/2. A faster algorit
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wiki
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encyclopedia
description:
original url:
https://en.wikipedia.org/wiki/Iterative_Viterbi_decoding
date created:
date modified:
2020-12-01T13:00:43Z
main entity:
{"identifier":"Q6094410","url":"https://www.wikidata.org/entity/Q6094410"}
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13
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