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Extraction of event-related signals from multichannel bioelectrical measurements

机译:从多通道生物电测量中提取事件相关信号

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摘要

Independent component analysis (ICA) is a powerful tool for separating signals from their mixtures. In this field, many algorithms were proposed, but they poorly use a priori information in order to find the desired signal. Here, we propose a fixed point algorithm which uses a priori information to find the signal of interest out of a number of sensors. We particularly applied the algorithm to cancel cardiac artifacts from a magnetoencephalogram.
机译:独立成分分析(ICA)是用于从混合信号中分离信号的强大工具。在该领域中,提出了许多算法,但是它们很少使用先验信息来找到期望的信号。在这里,我们提出了一种定点算法,该算法使用先验信息从多个传感器中找到感兴趣的信号。我们特别应用了该算法来消除脑磁图上的心脏伪影。

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