Extraction of the Fetal Electrocardiogram Using Dynamic Neural Networks

Detalles Bibliográficos
Parent link:	Biomedical Engineering.— , 1967- Vol. 50, iss. 6.— 2017.— [P. 371–375]
Autor Principal:	Devyatykh D. V. Dmitry Vladimirovich
Autor Corporativo:	Национальный исследовательский Томский политехнический университет (ТПУ) Институт неразрушающего контроля (ИНК) Учебно-методический отдел (УМО)
Outros autores:	Gerget O. M. Olga Mikhailovna
Summary:	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
Idioma:	inglés
Publicado:	2017
Subjects:	электронный ресурс труды учёных ТПУ экстракция электрокардиограммы нейтронные сети
Acceso en liña:	http://dx.doi.org/10.1007/s10527-017-9658-y
Formato:	Electrónico Capítulo de libro
KOHA link:	https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=654338

Descripción
Summary:	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
DOI:	10.1007/s10527-017-9658-y

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