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Characteristics of Question of Blind Source Separation Using Moore-Penrose Pseudoinversion for Reconstruction of EEG Signal

机译：使用MoEG信号重建莫雷彭偶伪倾向盲源分离问题的特征

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The paper presents question of blind source separation encountered by researchers aiming to determine location of generation electric activity in human brain as a source signal characteristic for given neuron fraction. To that end, Blind Signal Separation (BSS) technique with Moore-Penrose pseudoinversion was presented. The technique is useful for reconstruction of EEG signal. For the experimental purpose, sLORETA algorithm was also used to identify sources as a part of the inverse problem.

机译：本文提出了研究人员遇到的盲来源分离问题，旨在确定人脑中的发电作为给定神经元分数的源信号特性的位置。为此，介绍了具有摩尔猪Pseudoinversion的盲信号分离（BSS）技术。该技术可用于重建EEG信号。对于实验目的，SLORETA算法也用于识别作为逆问题的一部分的来源。

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《International Conference Automation》|2017年|xiv 606 pages|共8页
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Szczepan Paszkiel;
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中图分类 TP273-532;
关键词
Moore-Penrose pseudoinversion; EEG signal; Blind signal separation;

机译：Moore-Penrose伪倾向;脑电图信号;盲信号分离;

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专利

1. Blind Source Separation Techniques Based Eye Blinks Rejection in EEG Signals [J] . Ahmed Kareem Abdullah, Zhang Chao Zhu, Lian Siyao, Information Technology Journal . 2014,第3期

机译：基于盲源分离技术的脑电信号眨眼抑制
2. Blind Source Separation Techniques Based Eye Blinks Rejection in EEG Signals [J] . Ahmed Kareem Abdullah, Zhang Chao Zhu, Lian Siyao, Information Technology Journal . 2014,第3期

机译：基于盲源分离技术的脑电信号眨眼抑制
3. Non- Linear Principal Component Analysis Neural Network for Blind Source Separation of EEG Signals [J] . Saad A. Al-Shaban, Muaid S. Al-Faysale, Auns Qusai H. Al- Neami Research journal of applied science, engineering and technology . 2010,第2期

机译：脑电信号盲源分离的非线性主成分分析神经网络
4. Characteristics of Question of Blind Source Separation Using Moore-Penrose Pseudoinversion for Reconstruction of EEG Signal [C] . Szczepan Paszkiel International Conference Automation . 2017

机译：使用MoEG信号重建莫雷彭偶伪倾向盲源分离问题的特征
5. Blind Source Separation of Speech Signals: Exploiting Second Order Statistics [D] . Madanagopal, Vishaal. 2018

机译：语音信号的盲来源分离：利用二阶统计
6. Source-based neurofeedback methods using EEG recordings: training altered brain activity in a functional brain source derived from blind source separation [O] . David J. White, Marco Congedo, Joseph Ciorciari 2014

机译：使用脑电图记录的基于源的神经反馈方法：在源自盲源分离的功能性脑源中训练改变的大脑活动
7. Application Of Ica For Separation Of Artifacts In Meg/Eeg Signals By Blind Source Separation Using Improved Particle Swarm Optimizer [O] . Naresh Kumar A., Jayakrishnan G. 2012

机译：改进的粒子群优化算法在盲源分离中分离ICA在Meg / Eeg信号分离中的应用
8. Audio Signal Separation Using Blind Source Separation Techniques [R] . Kadambe, S., Owechko, Y. 1999

机译：采用盲源分离技术的音频信号分离

Characteristics of Question of Blind Source Separation Using Moore-Penrose Pseudoinversion for Reconstruction of EEG Signal

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