Algorithms for high order hidden Markov modelling

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dc.contributor.authordu Preez J.A.
dc.date.accessioned2011-05-15T15:57:31Z
dc.date.available2011-05-15T15:57:31Z
dc.date.issued1997
dc.description.abstractWe detail an algorithm that transforms any higher order hidden Markov model (HMM) to an equivalent first order HMM. This makes it possible to process higher order HMMs with standard techniques applicable to first order models. Based on this equivalence, a fast incremental algorithm is developed for training higher order HMMs from lower order approximations, thereby avoiding the training of redundant parameters. This makes training of high order HMMs practical for many applications.
dc.description.versionConference Paper
dc.identifier.citationProceedings of the South African Symposium on Communications and Signal Processing, COMSIG
dc.identifier.urihttp://hdl.handle.net/10019.1/10443
dc.subjectApproximation theory
dc.subjectMarkov processes
dc.subjectMathematical models
dc.subjectFast incremental algorithms
dc.subjectHidden Markov model (HMM)
dc.subjectAlgorithms
dc.titleAlgorithms for high order hidden Markov modelling
dc.typeConference Paper
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