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The consensus string problem and the complexity of comparing hidden Markov models

Abstract:

The basic theory of hidden Markov models was developed and applied to problems in speech recognition in the late 1960s, and has since then been applied to numerous problems, e.g. biological sequence analysis. Most applications of hidden Markov models are based on efficient algorithms for computing the probability of generating a given string, or computing the most likely path generating a given string. In this paper we consider the problem of computing the most likely string, or consensus str...

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Authors


Lyngsø, RB More by this author
Pedersen, CNS More by this author
Journal:
Journal of Computer and System Sciences
Volume:
65
Issue:
3
Pages:
545-569
Publication date:
2003
DOI:
ISSN:
0022-0000
URN:
uuid:3242a310-ff87-4b83-a9cb-7330e9decda9
Source identifiers:
104729
Local pid:
pubs:104729
Language:
English

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