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Statements

Subject Item
n2:RIV%2F68407700%3A21230%2F04%3A03099084%21RIV%2F2005%2FMSM%2F212305%2FN
rdf:type
n14:Vysledek skos:Concept
dcterms:description
Není k dispozici We present a unsupervised learning algorithm based on continuous Hidden Markov Models (HMM) to automatically classify Holter signals based on their morphology. Our proposed method automatically detect and separate the significant beats by means of hierarchical clustering scheme. Due to the convergence and numeric problems of a classical local optimization technique, we have implemented a novel approach for the global training of HMM by simulated annealing We present a unsupervised learning algorithm based on continuous Hidden Markov Models (HMM) to automatically classify Holter signals based on their morphology. Our proposed method automatically detect and separate the significant beats by means of hierarchical clustering scheme. Due to the convergence and numeric problems of a classical local optimization technique, we have implemented a novel approach for the global training of HMM by simulated annealing
dcterms:title
Není k dispozici Unsupervised Learning of Holter ECG signals using HMM optimized by simulated annealing Unsupervised Learning of Holter ECG signals using HMM optimized by simulated annealing
skos:prefLabel
Unsupervised Learning of Holter ECG signals using HMM optimized by simulated annealing Není k dispozici Unsupervised Learning of Holter ECG signals using HMM optimized by simulated annealing
skos:notation
RIV/68407700:21230/04:03099084!RIV/2005/MSM/212305/N
n3:strany
60 ; 62
n3:aktivita
n20:Z
n3:aktivity
Z(MSM 210000012)
n3:dodaniDat
n17:2005
n3:domaciTvurceVysledku
n7:2793172 n7:9431446
n3:druhVysledku
n8:D
n3:duvernostUdaju
n18:S
n3:entitaPredkladatele
n4:predkladatel
n3:idSjednocenehoVysledku
591481
n3:idVysledku
RIV/68407700:21230/04:03099084
n3:jazykVysledku
n9:eng
n3:klicovaSlova
ECG; Hidden Markov Models; Simulated Annealing
n3:klicoveSlovo
n10:ECG n10:Simulated%20Annealing n10:Hidden%20Markov%20Models
n3:kontrolniKodProRIV
[4D0F3D4CD9C1]
n3:mistoKonaniAkce
Brno
n3:mistoVydani
Brno
n3:nazevZdroje
Analysis of Biomedical Signals and Images
n3:obor
n19:JC
n3:pocetDomacichTvurcuVysledku
2
n3:pocetTvurcuVysledku
6
n3:rokUplatneniVysledku
n17:2004
n3:tvurceVysledku
Al-ani, T. Lhotská, Lenka Cuesta Frau, D. Hamam, Y. Novák, Daniel Mico, P.
n3:typAkce
n5:EUR
n3:zahajeniAkce
2004-06-23+02:00
n3:zamer
n21:MSM%20210000012
s:numberOfPages
3
n11:hasPublisher
VUTIUM Press
n15:isbn
80-214-2633-0
n13:organizacniJednotka
21230