Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/111492
Título: gpdsHMM: a hidden Markov model toolbox in the Matlab Enviromen
Autores/as: David, S.
Ferrer, Miguel A. 
Travieso, Carlos Manuel 
Alonso Hernández, Jesús Bernardino 
Clasificación UNESCO: 3307 Tecnología electrónica
Palabras clave: Pattern recognition
Hidden Markov Model
Matlab Toolbox
Fecha de publicación: 2004
Conferencia: Complex systems intelligence and modern technological applications, Cherbourg, France, 22 september 2004
Resumen: A Hidden Markov Model (HMM) Toolbox within the Matlab environment is presented. In this toolbox, the conventional techniques for the continuous and discrete HMM are developed for the training as well as for the test phases. The ability to make different groups of components for the vector pattern is provided. Multilabeling techniques for the discrete HMM is also provided. The toolbox includes procedures suitable for the classical applications based on the HMM, as pattern recognition, speech recognition and DNA sequence analysis.
URI: http://hdl.handle.net/10553/111492
Fuente: Proceedings of Complex systems intelligence and modern technological applications, p. 476-479
Colección:Ponencias
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