脑电研究包括脑电正问题和脑电逆问题研究。
The study of electroencephalogram (EEG) includes forward solution of EEG and inverse problem of EEG.
脑电研究领域的两个关键问题是脑电正问题和脑电逆问题。
There are two key problems in the field of EEG, EEG forward problem and EEG inverse problem.
基于四阶累积量矩阵的子空间分解，提出了一种新的脑电逆问题算法。
In this paper, based on the fourth-order cumulant matrix, a new sub-space decomposition algorithm is proposed for the EEG inverse problem.
脑电逆问题是指利用脑电图(EEG)数据去反演可以反映脑电活动等效偶极子源的参数信息。
Inverse problem of EEG means using EEG data to get the information of equivalent dipole sources that can reflect the activity of EEG.
仿真结果表明，在处理一个或两个源场的情况下，如果迭代初值选择合理，非线性局域优化方法可以有效地解决脑电逆问题。
Computer simulation demonstrates that nonlinear local optimization methods are effective for EEG inverse solution if the source number is one or two and the initial iterative values are reasonable.
就椭球头模型进行脑电正问题和逆问题进行推演。
To the ellipsoid model solve the forward problem and inverse problem.
就椭球头模型进行脑电正问题和逆问题进行推演。
To the ellipsoid model solve the forward problem and inverse problem.
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