Hidden Markov Models - An Introduction in the context of biomedical signal interpretation research

Research output: Book/ReportReport

Abstract

Hidden Markov Models (HMMs) have been around for quite some time as a tool to classify data and study the mechanisms that produce those data. Traditionally HMMs have been used in speech recogni-tion, but plenty of other application examples are available. Nowadays their application in BioIT is per-haps the most important field. This document aims to provide an introduction to the HMM concept and give an idea of their potential applicability in BSI (Biosignal Interpretation) research. A short introduc-tion to HMMs is provided with the emphasis on practical use. An overview of available software and potential application areas completes this document.
Original languageEnglish
Place of PublicationTampere
PublisherVTT Technical Research Centre of Finland
Number of pages22
Publication statusPublished - 2002
MoE publication typeD4 Published development or research report or study

Publication series

SeriesVTT Information Technology. Research Report
NumberTTE5-2001-34

Fingerprint

software
document
speech

Cite this

van Gils, M. (2002). Hidden Markov Models - An Introduction in the context of biomedical signal interpretation research. Tampere: VTT Technical Research Centre of Finland. VTT Information Technology. Research Report, No. TTE5-2001-34
van Gils, Mark. / Hidden Markov Models - An Introduction in the context of biomedical signal interpretation research. Tampere : VTT Technical Research Centre of Finland, 2002. 22 p. (VTT Information Technology. Research Report; No. TTE5-2001-34).
@book{ed76af104cb34af492b6192e75ba84eb,
title = "Hidden Markov Models - An Introduction in the context of biomedical signal interpretation research",
abstract = "Hidden Markov Models (HMMs) have been around for quite some time as a tool to classify data and study the mechanisms that produce those data. Traditionally HMMs have been used in speech recogni-tion, but plenty of other application examples are available. Nowadays their application in BioIT is per-haps the most important field. This document aims to provide an introduction to the HMM concept and give an idea of their potential applicability in BSI (Biosignal Interpretation) research. A short introduc-tion to HMMs is provided with the emphasis on practical use. An overview of available software and potential application areas completes this document.",
author = "{van Gils}, Mark",
year = "2002",
language = "English",
series = "VTT Information Technology. Research Report",
publisher = "VTT Technical Research Centre of Finland",
number = "TTE5-2001-34",
address = "Finland",

}

van Gils, M 2002, Hidden Markov Models - An Introduction in the context of biomedical signal interpretation research. VTT Information Technology. Research Report, no. TTE5-2001-34, VTT Technical Research Centre of Finland, Tampere.

Hidden Markov Models - An Introduction in the context of biomedical signal interpretation research. / van Gils, Mark.

Tampere : VTT Technical Research Centre of Finland, 2002. 22 p. (VTT Information Technology. Research Report; No. TTE5-2001-34).

Research output: Book/ReportReport

TY - BOOK

T1 - Hidden Markov Models - An Introduction in the context of biomedical signal interpretation research

AU - van Gils, Mark

PY - 2002

Y1 - 2002

N2 - Hidden Markov Models (HMMs) have been around for quite some time as a tool to classify data and study the mechanisms that produce those data. Traditionally HMMs have been used in speech recogni-tion, but plenty of other application examples are available. Nowadays their application in BioIT is per-haps the most important field. This document aims to provide an introduction to the HMM concept and give an idea of their potential applicability in BSI (Biosignal Interpretation) research. A short introduc-tion to HMMs is provided with the emphasis on practical use. An overview of available software and potential application areas completes this document.

AB - Hidden Markov Models (HMMs) have been around for quite some time as a tool to classify data and study the mechanisms that produce those data. Traditionally HMMs have been used in speech recogni-tion, but plenty of other application examples are available. Nowadays their application in BioIT is per-haps the most important field. This document aims to provide an introduction to the HMM concept and give an idea of their potential applicability in BSI (Biosignal Interpretation) research. A short introduc-tion to HMMs is provided with the emphasis on practical use. An overview of available software and potential application areas completes this document.

M3 - Report

T3 - VTT Information Technology. Research Report

BT - Hidden Markov Models - An Introduction in the context of biomedical signal interpretation research

PB - VTT Technical Research Centre of Finland

CY - Tampere

ER -

van Gils M. Hidden Markov Models - An Introduction in the context of biomedical signal interpretation research. Tampere: VTT Technical Research Centre of Finland, 2002. 22 p. (VTT Information Technology. Research Report; No. TTE5-2001-34).