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  • In the study, an influence of the number of states of a hidden Markov model on recognition efficiency was examined. The model was used for detection of acute myocardial ischemia from ECG signals. The time-frequency wavelet transform was applied to preprocess the recorded data. Thus, HMMs were able to recognize subtle electrophysiological changes caused by ischemia. The models with selected number of states were tested on signals from 10 experiments. An optimal number of states K=3 was found in the studyy.
  • In the study, an influence of the number of states of a hidden Markov model on recognition efficiency was examined. The model was used for detection of acute myocardial ischemia from ECG signals. The time-frequency wavelet transform was applied to preprocess the recorded data. Thus, HMMs were able to recognize subtle electrophysiological changes caused by ischemia. The models with selected number of states were tested on signals from 10 experiments. An optimal number of states K=3 was found in the studyy. (en)
  • In the study, an influence of the number of states of a hidden Markov model on recognition efficiency was examined. The model was used for detection of acute myocardial ischemia from ECG signals. The time-frequency wavelet transform was applied to preprocess the recorded data. Thus, HMMs were able to recognize subtle electrophysiological changes caused by ischemia. The models with selected number of states were tested on signals from 10 experiments. An optimal number of states K=3 was found in the studyy. (cs)
Title
  • The Number of States of the Hidden Markov Model in ECG Signal Processing
  • The Number of States of the Hidden Markov Model in ECG Signal Processing (en)
  • The Number of States of the Hidden Markov Model in ECG Signal Processing (cs)
skos:prefLabel
  • The Number of States of the Hidden Markov Model in ECG Signal Processing
  • The Number of States of the Hidden Markov Model in ECG Signal Processing (en)
  • The Number of States of the Hidden Markov Model in ECG Signal Processing (cs)
skos:notation
  • RIV/00216305:26220/02:PU29414!RIV06-GA0-26220___
http://linked.open.../vavai/riv/strany
  • 95-98
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(GA102/01/1494), Z(MSM 262200022)
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
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http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 656144
http://linked.open...ai/riv/idVysledku
  • RIV/00216305:26220/02:PU29414
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Electrocardiographic signal, wavelet transform, vector quantization, hidden Markov model (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [50E2A899E840]
http://linked.open...v/mistoKonaniAkce
  • Zámek Nečtiny
http://linked.open...i/riv/mistoVydani
  • Plzeň
http://linked.open...i/riv/nazevZdroje
  • Elektrotechnika a informatika 2002
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Provazník, Ivo
  • Bardoňová, Jana
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
http://linked.open...n/vavai/riv/zamer
number of pages
http://purl.org/ne...btex#hasPublisher
  • Západočeská Univerzita
https://schema.org/isbn
  • 80-7082-904-4
http://localhost/t...ganizacniJednotka
  • 26220
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