Extraction of the Fetal Electrocardiogram Using Dynamic Neural Networks; Biomedical Engineering; Vol. 50, iss. 6
| Parent link: | Biomedical Engineering.— , 1967- Vol. 50, iss. 6.— 2017.— [P. 371–375] |
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| Κύριος συγγραφέας: | |
| Συγγραφή απο Οργανισμό/Αρχή: | |
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| Περίληψη: | Title screen This article presents a nonlinear dynamics model for discriminating the sources of the maternal abdominal elec-trocardiogram (aECG). The coefficients of the separating matrix were determined by training a neural network. This method provides efficient extraction of the fetal electrocardiogram (fECG) independently of the choice of recording point, input signal duration, or number of independent leads. Режим доступа: по договору с организацией-держателем ресурса |
| Γλώσσα: | Αγγλικά |
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2017
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| Διαθέσιμο Online: | http://dx.doi.org/10.1007/s10527-017-9658-y |
| Μορφή: | Ηλεκτρονική πηγή Κεφάλαιο βιβλίου |
| KOHA link: | https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=654338 |
| Περίληψη: | Title screen This article presents a nonlinear dynamics model for discriminating the sources of the maternal abdominal elec-trocardiogram (aECG). The coefficients of the separating matrix were determined by training a neural network. This method provides efficient extraction of the fetal electrocardiogram (fECG) independently of the choice of recording point, input signal duration, or number of independent leads. Режим доступа: по договору с организацией-держателем ресурса |
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| DOI: | 10.1007/s10527-017-9658-y |