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小波域的盲源分离，可以有效地去除噪声，尤其是在胎儿心电提取方面-Wavelet domain blind source separation can effectively remove the noise, especially in regard to extraction of fetal ECG
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针对目前很多人做胎心电分离是缺少合适的心电数据，本人上传了一个很适合的从孕妇胸部和腹部通过电极采集到的心电信号。-At present, many people do for the fetal heart electrical separation is the lack of appropriate ECG data, I upload a very suitable from the chest and abdomen of pregnant women collected through
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神经网络算法RBF分离母体心电和胎儿心电信号-RBF neural network algorithm for separation of maternal ECG and fetal ECG
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基于独立变量分析的快速ICA算法分离母体与胎儿心电信号-Based on independent analysis of the fast ICA algorithm variable maternal and fetal ECG separation
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This paper presents a new algorithm to extract
the fetal ECG from an ECG recorded on the
mother’s abdomen. The algorithm consists of
two steps: first, ECG of fetus is extracted from
the original signal using a two-level wavelet
transform. W
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Fetal electrocardiogram (fetal ECG) extraction is an interesting as well as a difficult problem in signal processing. This forms one important application of Independent Component Analysis (ICA) or Blind Source Separation (BSS),
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ECG fetal separation ...Using wavelet
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The study presents a method to separate the fetal electrocardiograph(FECG) from
concomitant maternal electrocardiograph (MECG) by using Fast Independent component
analysis(ICA) algorithm of Blind Signal Separation. Current methods of extracting f
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The fetal monitoring in parturient period is directly related to the safety of pregnant women and
fetuses. Fetal electrocardiogram (FECG) is an objective indicator as a reflection of intrauterine
physiological activities. The ECG signals of mater
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