. "26220" . . "The Number of States of the Hidden Markov Model in ECG Signal Processing" . "[50E2A899E840]" . "2002-10-23+02:00"^^ . "The Number of States of the Hidden Markov Model in ECG Signal Processing"@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 . . "The Number of States of the Hidden Markov Model in ECG Signal Processing" . "4"^^ . "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 . "Z\u00E1pado\u010Desk\u00E1 Univerzita" . . . "Electrocardiographic signal, wavelet transform, vector quantization, hidden Markov model"@en . "Bardo\u0148ov\u00E1, Jana" . . . "Elektrotechnika a informatika 2002" . . "The Number of States of the Hidden Markov Model in ECG Signal Processing"@cs . "80-7082-904-4" . "Plze\u0148" . . . . "656144" . "2"^^ . "The Number of States of the Hidden Markov Model in ECG Signal Processing"@en . "2"^^ . . "RIV/00216305:26220/02:PU29414" . . . "RIV/00216305:26220/02:PU29414!RIV06-GA0-26220___" . "Provazn\u00EDk, Ivo" . . "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." . . . "Z\u00E1mek Ne\u010Dtiny" . . . "95-98" . "P(GA102/01/1494), Z(MSM 262200022)" . "The Number of States of the Hidden Markov Model in ECG Signal Processing"@cs .