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Application of decorrelation-independent component analysis to biomagnetic multi-channel measurements

机译:独立于解相关的成分分析在生物磁多通道测量中的应用

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摘要

Biomagnetic multi-channel recordings are typically a superposition of signals from several biological sources of interest and from biological and technical noise sources. Besides averaging, source localization, and spectral analysis to name only a few methods, independent component analysis is an established tool to resolve the superposition present in raw biomagnetic data on a purely statistical basis. Here the time-delayed decorrelation-independent component analysis algorithm is applied to exemplary magnetocardiographic and magnetoencephalographic data and the successful signal separation is demonstrated.
机译:生物磁多通道记录通常是来自多个感兴趣的生物源以及生物和技术噪声源的信号的叠加。除了平均,源定位和频谱分析等仅举几种方法外,独立成分分析是一种建立的工具,可以在纯粹的统计基础上解决原始生物磁数据中存在的叠加问题。在此,将时滞相关性独立的成分分析算法应用于示例性的心电图和脑磁图数据,并证明了成功的信号分离。

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