Implementing EM and Viterbi algorithms for Hidden Markov Model in linear memory

BACKGROUND: The Baum-Welch learning procedure for Hidden Markov Models (HMMs) provides a powerful tool for tailoring HMM topologies to data for use in knowledge discovery and clustering. A linear memory procedure recently proposed by Miklós, I. and Meyer, I.M. describes a memory sparse version of th...

Descripción completa

Detalles Bibliográficos
Autores principales: Churbanov, Alexander, Winters-Hilt, Stephen
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2008
Materias:
Methodology Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2430973/
https://www.ncbi.nlm.nih.gov/pubmed/18447951
http://dx.doi.org/10.1186/1471-2105-9-224

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2430973/
https://www.ncbi.nlm.nih.gov/pubmed/18447951
http://dx.doi.org/10.1186/1471-2105-9-224

Ejemplares similares