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ICA-Based EEG Spatio-temporal Dipole Source Localization: A Model Study

机译:基于ICA的EEG时空偶极源定位:模型研究

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In this paper, we examine the performance of an Independent Component Analysis (ICA) based dipole localization approach to localize multiple source dipoles under noisy environment. Uncorrelated noise of up to 40% was added to scalp EEG signals. The performance of the ICA-based algorithm is compared with the conventional localization procedure using Simplex method. The present simulation results indicate the robustness of the ICA-based approach in localizing multiple dipoles of independent sources.
机译:在本文中,我们研究了基于独立分量分析(ICA)的偶极定位方法的性能,以在嘈杂的环境下定位多个源偶极子。向SIGP EEG信号中添加了高达40%的不相关噪声。使用Simplex方法将基于ICA的算法的性能与传统定位过程进行了比较。目前的仿真结果表明了基于ICA的稳健性在本地化独立源的多个偶极子中的鲁棒性。

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